D3.3 Advanced models and technologies of local storage and

Deliverable 3.3 Advanced models and technologies of

local storage and electromobility

Delivery Date: October 2020

D3.3 Advanced models and technologies of local storage and electromobility 1

*Type: P: Prototype; R: Report; D: Demonstrator; O: Other.

**Security Class: PU: Public; PP: Restricted to other programme participants (including the Commission); RE: Restricted to

a group defined by the consortium (including the Commission); CO: Confidential, only for members of the consortium

(including the Commission).

Title Document Version

D3.3 Advanced models and technologies of local storage and electromobility 1.0

Project Number Project Acronym Project Title

H2020-824424 COMPILE COMPILE: Integrating community power in energy islands

Contractual Delivery Date Actual Delivery Date Deliverable Type*-Security**

31 October 2020 31 October 2020 R-PU

Responsible Organisation Contributing WP

Jure Ratej ETRL WP3

Abstract

The subject of this document is local energy storage systems implemented within the COMPILE project. Real

(Battery Energy Storage Systems) and virtual (electric vehicle batteries) energy storage systems are

implemented in two pilot sites (Luče and Križevci). The document describes the main characteristics of

implemented solutions: technical features, system architecture with interactions with external components,

process flows, algorithms, test procedures, and requirements for installation, commissioning and use.

Keywords

Local Energy Systems, Energy storage, Demand response, Interoperability.


This project has received funding from the

European Union’s Horizon 2020 Research and Innovation Programme

under Grant Agreement № 824424.

More information available at https://www.compile-project.eu/

Copyright Statement

The work described in this document has been conducted within the COMPILE project. This document reflects only the COMPILE Consortium view and the European Union is not responsible for any use that may be made of the information it contains.

This document and its content are the property of the COMPILE Consortium. All rights relevant to this document are determined by the applicable laws. Access to this document does not grant any right or license on the document or its contents. This document or its contents are not to be used or treated in any manner inconsistent with the rights or interests of the COMPILE Consortium or the Partners detriment and are not to be disclosed externally without prior written consent from the COMPILE Partners.

Each COMPILE Partner may use this document in conformity with the COMPILE Consortium Grant Agreement provisions.

Revision Date Description Author (Organisation)

V0.0 27.05.2020 New document; ToC and contributors Jure Ratej (ETRL)

V0.1 21.08.2020 First draft (Chapters 4 and 5) Gašper Artač, Igor Jan, Borut Jereb (PETR)

Jure Ratej, Borut Mehle (ETRL)

V0.2 14.09.2020 Second draft (Chapter 3) Virgilio Gómez, Diego Garcia (ETRA)

Boris Pavlin (ZEZ)

V0.3 08.10.2020 Chapter 1, first complete draft, instructions

to contributors for amendments Tomi Medved (IRI UL), Jure Ratej (ETRL)

V0.4 13.10.2020 Final draft, ready for review Jure Ratej (ETRL)

V0.5 19.10.2020 Internal review remarks Tomi Medved (IRI UL), Gašper Artač (PET)

V1.0 31.10.2020 Final version (submitted) Jure Ratej (ETRL), Marjana Harej (UL)


EXECUTIVE SUMMARY

The present deliverable summarises the outcomes of activities of WP3 Modelling, control and

digitalization of the LES, specifically of its task T3.3 Advanced models and technologies of local storage

and electromobility.

The subject of the document is the implementation of real (batteries) and virtual (electric vehicle

charging) storage technologies with associated control functionalities at COMPILE pilot sites:

• Real storage in Križevci: two lithium-ion batteries, each with 8,8 kWh usable capacity and

maximum charge/discharge power 5,0 kW;

• Real storage in Luče: lithium-ion battery with 333 kWh usable capacity and maximum

charge/discharge power 150 kVA. Also, five home battery systems were installed and

integrated with COMPILE tools for home energy management;

• Virtual storage in Križevci and Luče: exploitation of load flexibility of the electric vehicle

charging process. At each site, one charging station is installed with the capability to charge

two electric vehicles at a time, each of them with a maximum charging power of 22 kW.

Besides, in Luče 9 existing private AC charging stations (installed in households) with a rated

maximum power of 22 kW each will be integrated with the COMPILE system.

In Križevci, the battery storage system will be installed in Technology Park that consists of five

buildings. The local energy system is controlled by a common building energy management system

(ETRA HomeRule) which controls the battery, a 30 kW photovoltaic generation unit and other

controllable loads within the buildings. Battery storage inverter communicates periodically to

HomeRule the data about planned operation and status of the battery; HomeRule calculates the

optimum operation profile of battery storage and sends it to storage inverter. In this process also grid

monitoring and control system (ETRA GridRule) is involved, which sends (if required to improve the

grid operation) requests for activation of the building’s flexibility reserves to HomeRule.

As of October 2020, the storage system has been purchased. The specific details of its installation — physical location, grid connection, communication with the devices, etc. — is already decided; the installation will begin in November 2020.

Before installation, the storage system was factory tested according to standard procedures. After

installation, the same tests will be repeated and additional tests (operation in island mode and under

usual operation conditions) will be performed. After commissioning, no special maintenance

interventions are required. As the operation is fully automated, only daily remote monitoring and

monthly visual inspection is recommended.

In Luče, the battery storage system consists of a 333 kWh battery connected to the low voltage busbar

of the distribution transformer station. Advanced control mechanisms are implemented in the storage

system’s controller, which enables the storage system to operate in two modes:

• According to set points received from grid monitoring and control system (PETROL GridRule),

• Independent control in the case the communication with GridRule is not available.

In the independent control mode, several control algorithms are applied, such as peak load shaving,

reactive power compensation, frequency control and self-sufficiency & island operation. Besides the

determination of the storage system’s operation profile, the control logic also monitors the conditions

in the grid and executes load shedding when the local energy system operates in island mode.

The Luče battery storage system was installed in February 2020. Before shipment to the COMPILE pilot

site, the factory tests were executed to verify the correct performance of the system: visual checks,

initialisation of devices (controller, communications, inverters), verification of battery racks’ voltage,


load tests, and thermal tests. After installation, on-site tests were executed to check operation in a

real environment. The tests were focused on the manual and remote control of the operation, zero

load operation, and round trip efficiency.

During operation of the system, regular maintenance is required in monthly, half-yearly and yearly

time intervals to maintain the battery system in good condition and avoid malfunctions in operation

by early detection of eventual deficiencies.

Electric vehicle charging as virtual storage is implemented in Luče and Križevci. At both locations, one

charging station is installed which enables the simultaneous charging of two electric vehicles, each

with a maximum power of 22 kW. The charging control centre (EVRule) monitors the operation of

charging infrastructure and determines the initial charging load profiles and associated load flexibility

capacity with consideration of the following input information:

• anticipated time of departure: inserted by users via smartphone or charging station’s touch

screen;

• required energy to be delivered to electric vehicle till departure time: EVRule calculates the

value by statistical methods applied on data about the user’s past charging load profiles;

• maximum power that can be delivered to an electric vehicle: calculated based on data about

technical characteristics of power supply and charging equipment (rated currents of power

supply to charging station, equipment in charging station and charging cable) inserted in

EVRule during the setup of the system;

• maximum power that can be drawn by an electric vehicle: depends on characteristics of

charger installed in the electric vehicle. The value is measured by the charging station.

The initial charging load profile is communicated to grid monitoring and control systems (GridRule). In

the case the GridRule requires modification of the initial charging load profile (i.e. activation of load

flexibility), the EVRule calculates a new profile that matches with GridRule’s requirement and thus

contributes to reliable and optimum grid operation.

After the standard factory testing of charging stations (visual inspection, verification of proper

execution of basic charging processes, correct operation of communication, user interfaces and

metering devices, and) the stations were delivered to pilot sites. Within the next months the system

setup (communication interfaces, data about charging stations and local power supply) will be

executed, followed by operation tests in the real environment. During operation, no extensive

maintenance of the system is required; continuous checking of reports and event logs together with

yearly visual inspection of charging equipment assures timely detection of potential malfunctions in

operation.

The battery energy storage and electric vehicle charging systems, designed as presented in the

document, can actively support the operation of local energy systems. With the exploitation of storage

systems’ load flexibility, the energy communities will be able to achieve a higher level of reliability of

local grid operation, increase penetration of renewable energy sources’ production and optimise the

costs associated with power production and supply to final customers.

The results of activities of T3.3 represent a quality foundation for later project activities directly

related to deployment and operation of various systems at pilot sites (T3.4 Software integration, WP5

Pilot sites and WP6 Impact assessment). Furthermore, the presented functionalities of storage

systems will support the energy communities and grid operators at pilot sites in the development of

business models which will lead to the achievement of their goals set within the project.


Table of contents

EXECUTIVE SUMMARY ...................................................................................................... 3

1 INTRODUCTION ......................................................................................................... 8

Purpose of the document ........................................................................................... 8

Scope of the document ............................................................................................... 8

Structure of the document .......................................................................................... 8

2 REAL AND VIRTUAL STORAGE .................................................................................... 9

General information about storage technologies ....................................................... 9

Real storage - technologies ......................................................................................... 9

Virtual storage - technologies ................................................................................... 11

EV charging .................................................................................................................... 12

Types and purpose of storage implemented in Compile .......................................... 19

Pilot site Luče ................................................................................................................ 19

Pilot site Križevci ........................................................................................................... 20

3 REAL STORAGE IN KRIŽEVCI ..................................................................................... 20

General information .................................................................................................. 20

Architecture ............................................................................................................... 23

Process flows and algorithms .................................................................................... 25

External process flow diagram and interfaces .............................................................. 25

Internal process flow diagram, interfaces, and control algorithms .............................. 27

Factory testing ........................................................................................................... 28

Requirements for installation and commissioning ................................................... 28

Requirements for use ................................................................................................ 29

4 REAL STORAGE IN LUČE ............................................................................................ 29


Architecture ............................................................................................................... 31


Process flow (control) diagram ..................................................................................... 34

External interfaces ........................................................................................................ 35

Internal interfaces ......................................................................................................... 35

Interfaces to COMPILE tools ......................................................................................... 36

Internal control algorithms ........................................................................................... 37


Factory testing ........................................................................................................... 37


Technical requirements ................................................................................................ 39

Non-technical requirements ......................................................................................... 39

Field tests ...................................................................................................................... 39


5 VIRTUAL STORAGE – EV CHARGING .......................................................................... 41


System Architecture .................................................................................................. 43

Subordinated EVRule .................................................................................................... 43

Independent EVRule ..................................................................................................... 44


Actors and components involved in EVRule operation ................................................ 46

Interfaces between actors and components ................................................................ 47

EV charging process flow .............................................................................................. 48

Factory testing ........................................................................................................... 53

Component tests ........................................................................................................... 53

Interface and closed-loop lab tests ............................................................................... 54


Installation .................................................................................................................... 54

System setup ................................................................................................................. 55

Field tests ...................................................................................................................... 56


6 CONCLUSIONS ......................................................................................................... 57

7 REFERENCES AND ACRONYMS ................................................................................. 59

References ................................................................................................................. 59

Acronyms ................................................................................................................... 59

8 ANNEX A: EVRULE - INSTRUCTIONS FOR USE BY EV USERS ........................................ 61

General requirements ............................................................................................... 61

Adding EV types to be used by EV user ......................................................................... 61

Identification of EV user before charging ..................................................................... 65

Insertion of departure time .......................................................................................... 65

Selection of EV type to be charged ............................................................................... 65


LIST OF FIGURES Figure 1: Basic scenarios of EV charging load scheduling ..................................................................... 14

Figure 2: Energy storage at planned continuous charging and actual forced charging........................ 16

Figure 3: Energy storage at planned continuous charging and actual postponed charging................. 16

Figure 4: Energy storage at planned continuous charging and actual combined charging .................. 17

Figure 5: Energy storage at planned forced charging and actual continuous charging ....................... 18

Figure 6: Energy storage at planned forced charging and actual postponed charging ........................ 19

Figure 7: Energy storage at planned forced charging and actual combined charging ......................... 19

Figure 8: Križevci Technology Park ........................................................................................................ 21

Figure 9: Aerial view of the five buildings of the Križevci Technology Park ......................................... 22

Figure 10: Križevci Technology Park storage system overview ............................................................ 23

Figure 11: Križevci Technology Park in HomeRule ................................................................................ 24

Figure 12: Križevci Technology Park detail in HomeRule ...................................................................... 25

Figure 13: HomeRule external process flow for Križevci Technology Park ........................................... 26

Figure 14: HomeRule internal process flow .......................................................................................... 27

Figure 15: BESS installed in Luče ........................................................................................................... 29

Figure 16: BESS connection point inside the transformer station ........................................................ 30

Figure 17: Household battery systems ................................................................................................. 31

Figure 18: BESS system overview .......................................................................................................... 32

Figure 19: BESS internal components ................................................................................................... 33

Figure 20: Home energy management system (HomeRule) ................................................................. 33

Figure 21: Integrated assets in GridRule ............................................................................................... 34

Figure 22: Luče storage process flow .................................................................................................... 35

Figure 23: BESS scheduler module, Production and consumption forecast module results with actual

flow ....................................................................................................................................................... 36

Figure 24: Load test............................................................................................................................... 37

Figure 25: Thermal test LCL filter .......................................................................................................... 38

Figure 26: Thermal test room temperature .......................................................................................... 38

Figure 27: Full cycle test ........................................................................................................................ 38

Figure 28: Results of BESS RTE test ....................................................................................................... 40

Figure 29: Charging station installed in Luče ........................................................................................ 42

Figure 30: Charging station installed in Križevci ................................................................................... 43

Figure 31: Simplified architecture of EV charging system (subordinated EVRule) ............................... 44

Figure 32: Charge Point Management System (operated by CPO) ....................................................... 45

Figure 33: Simplified architecture of EV charging system (independent EVRule) ................................ 46

Figure 34: Charging station’s user interface – Insertion of PIN code and departure time ................... 47

Figure 35: Smartphone screen - Selection of charging station and insertion of departure time ......... 47

Figure 36: Smartphone and tablet screens for monitoring of charging session ................................... 48

Figure 37: Types of charging station (wallbox – left, pillar – right) ...................................................... 54

Figure 38: Outdoor installation of charging station .............................................................................. 55


1 INTRODUCTION

PURPOSE OF THE DOCUMENT

The purpose of this document is to describe the real and virtual storage technologies that are or will

be implemented in the COMPILE project.

The document serves as an overview of mentioned systems to enable pilot sites managers to

understand the operation principles of storage technologies within the entire COMPILE ecosystem,

and with this to efficiently supervise their operation during the trial period (WP6 Impact assessment).

Furthermore, the goal of the document is to provide information about testing, deployment

procedures, and requirements about use of the systems, which will enable smooth execution of works

within WP5 Pilot sites (installation, integration with other COMPILE components, and undisturbed

operation of storage systems during the trial period and beyond).

The document was elaborated by ETRA, PET and ETRL, acting as suppliers and integrators of storage

technologies and related COMPILE ICT tools, with the contribution of IRI UL, which provided the

general description related to storage, and ZEZ, which provided information about technical

characteristics of devices installed at pilot site Križevci.

SCOPE OF THE DOCUMENT

The document deals with storage technologies implemented at COMPILE pilot sites (Luče and

Križevci). Both types of technology, namely real energy storage (battery energy storage systems) and

virtual storage (electric vehicles) are implemented at both mentioned pilot sites.

The document describes technical characteristics of storage devices, real system architectures

implemented at sites, interfaces between storage devices and external actors and devices (higher-

level control levels – GridRule, ComPilot and EVRule), process flows and algorithms implemented

either in storage devices or higher-level control levels, which assure an efficient integration of storage

with the local Energy Community’s grid.

Also, the document gives, for each technology, some preliminary information about testing of storage

systems to be implemented, and requirements to be followed for their installation, deployment and

commissioning.

STRUCTURE OF THE DOCUMENT

The document consists of two main parts: an introductory part (Chapter 2) and descriptions of

implemented solutions at pilot sites (Chapters 3, 4 and 5).

Chapter 2 REAL AND VIRTUAL STORAGE gives the general information about the various available

technologies for real and virtual storage that can be used to cover different energy islands’, their main

“pros and cons”. The chapter also provides the latest developments/trends in storage technologies.

Chapters 3 REAL STORAGE IN KRIŽEVCI, Chapter 4 REAL STORAGE IN LUČE and Chapter 5 VIRTUAL

STORAGE – EV CHARGING describe the architectures, process flows and algorithms of systems that

will be implemented at individual COMPILE pilot sites. At the end of each chapter the requirements

for testing, implementation, commissioning and use of the systems are described.


2 REAL AND VIRTUAL STORAGE

GENERAL INFORMATION ABOUT STORAGE TECHNOLOGIES

In this chapter, we present a short overview of various storage technologies and their applicability in the power system operation and energy islands. The storage can be divided into two main categories based on their physical characteristics:

• Real storage (i.e. stationary batteries) and

• Virtual storage (i.e. load shifting, applicable also to EV charging).

Energy storage can be used for two general functionalities:

• Grid operation support including ancillary services for:

o TSO - Frequency Containment Reserve (FCR), Automatic or Manual frequency restoration reserves (aFRR & mFRR), and power limitations/load shedding as demand response service for grid congestion management. The battery storage can also be used to help with the black start of the system.

o DSO – voltage regulation and grid congestion management in a low voltage network.

• Optimisation of prosumers production and consumption like minimisation of energy delivery costs, avoiding violation of internal network capacity or rated current of fuses,).

Stationary batteries come in a variety of designs for different applications, such as emergency power backup, telecommunications equipment, uninterruptible power supplies (UPS) and many others. The largest types of stationary batteries are used for electrical load levelling. These types of batteries store electrical energy during low demand or excess RES production and deliver it into the grid at times of peak power demand. The variety of uses also include the following services/solutions: UPS, Electricity wholesale market arbitrage, frequency regulation, reserve capacity, peak shaving, increasing end-consumer reliability, self-consumption or provide him with off-grid power supply (a combination of battery with solar PV).

The mainland electricity systems are large, very well interconnected systems with high system inertia and the ability to balance loads with generation resources over large geographical areas. Due to these characteristics, it is possible to have a competitive market for power and ancillary services.

While on the other hand, island and microgrid electricity systems are much smaller and defined based on the number of inhabitants. A microgrid is a group of interconnected loads and distributed energy resources within clearly defined electrical boundaries acting as a single controllable entity concerning the grid. A microgrid/energy island can connect/disconnect from the grid, enabling it to operate in grid-connected / island mode. The main shortcoming of energy islands is low inertia and that is why energy storage, especially battery that can provide quick response, is a suitable solution.

REAL STORAGE - TECHNOLOGIES

Improvements in materials and technology have greatly increased the performance and reliability of modern battery systems and at the same time dramatically reduced the associated cost. New technologies, like electrochemical capacitors, can be charged and discharged simultaneously and instantly, providing an almost unlimited lifespan.

Batteries can be classified into different categories based on chemical composition, size, form factor and use cases. Two major battery types are primary batteries and secondary batteries. Primary batteries have a much longer lifecycle than secondary batteries, are highly efficient, have low leakage and are small in size. Their main disadvantage is that they cannot be recharged and areas such


inappropriate for the load levelling applications. Secondary batteries are batteries whose chemical reactions can be reversed by applying a certain voltage to the battery in the reversed direction. These types of batteries can be used in powering small electrical appliances like mobile phones or as a heavy-duty battery in electric vehicles and other high drain applications. They can also be used as standalone power sources alongside inverters.

Secondary batteries are divided into several types based on their chemical structure. The chemistry determines the characteristics and attributes of the battery, which define also their applicability are: cycle life, shelf life, price, the energy density per mass, energy density per volume, temperature depended on characteristics, etc.

There are many different types of batteries, a lot of them still in the research phase, and here we just shortly describe the most used and promising ones:

• Lead-Acid is one of the oldest battery technologies and presents a low-cost alternative used in heavy-duty applications. The batteries are very heavy and large comparing to other types and are almost always used in non-portable applications such as solar panel energy storage, vehicle ignition, backup power and power generation and distribution.

PROS: Out of all types of batteries the Lead-Acid type batteries are the cheapest and simplest to manufacture. They are capable of delivering high power bursts with huge surge currents and have a relatively large power to weight ratio. Lead is also the most recycled metal, making lead batteries the only battery energy storage system (BESS) that can be almost completely recycled.

CONS: The main problem of Lead Acid batteries is that they have very low energy to volume ratio and energy to weight ratios which means that their size is big or rather huge for big powers needed in power system applications. Even though lead is one disadvantage of lead-acid batteries is also that lead is hazardous and restricted.

• Nickel-Metal Hybrid Batteries are typically used in high drain applications because of their high energy density mostly used in consumer electronics and was also used in first-generation fo EV cars, but were later

PROS: Unlike Nickel-Cadmium batteries, which were “predecessor” and main technology used in consumer electronics, this type of batteries is not susceptible to the memory effect.

CONS: Safety problems with overcharging and lower energy density in comparison with lithium-ion technology.

• Flow Battery/Redox batteries: is a type of electrochemical cell where chemical energy is provided by two chemical components dissolved in liquids that are pumped through the system on separate sides of a membrane. Ion exchange that produces electric current occurs through the membrane while both liquids circulate in their own respective space. There are two operation options of flow battery, it may be used like a fuel cell, where the charge is added to the system or like a rechargeable battery where an outside electric power source recharge the battery.

PROS: The biggest advantages are: flexible layout (separate power and energy components), long cycle life - near-unlimited longevity (no solid-to-solid phase transitions), quick response times, almost no overcharging or over-discharging risk (no need for "equalisation" – a process ensuring that all cells have an equal charge). Some types also offer easy state-of-charge determination (through voltage dependence on charge). They require low maintenance are safe and typically do not contain flammable electrolytes and which can be stored away from


the power stack. All these technical characteristics make flow batteries an appropriate choice for large-scale energy storage.

CONS: The two main disadvantages are their low energy density (you need large tanks of electrolyte to store useful amounts of energy) and their low charge and discharge rates (compared to other industrial electrode processes). The latter means that the electrodes and membrane separators need to be large, which increases costs. Current implementations are comparatively less powerful than other conventional rechargeable technologies, require more sophisticated electronics and have a lower efficiency.

• Fuel cell (Hydrogen) - A fuel cell is an electrochemical cell that converts the chemical energy of a fuel (often hydrogen) and an oxidizing agent (often oxygen) into electricity through a pair of redox reactions. Fuel cells are different from most batteries in requiring a continuous source of fuel and oxygen (usually from air) to sustain the chemical reaction. Fuel cells can produce electricity continuously for as long as fuel and oxygen are supplied.

PROS: The fuel cells' ability to quickly recharge fuel (Hydrogen) is the biggest advantage. Also, the capacity and power that it can produce are on the required level that is needed for various applications, from transportation (EV, buses,…) to power system applications (ideas of seasonal storage).

CONS: The full cell biggest advantage is also its biggest disadvantage. Hydrogen as a fuel is hazardous and it’s currently expensive to produce. The problem is also in the costs and energy needed to transport it safely.

• Lithium-ion batteries are one of the most popular types of rechargeable batteries and are most likely to be the “battery storage” of the future. They are very lightweight, possess high energy density, have little or no memory effect and have a low self-discharge compared to other battery types. They can be found in almost all newer consumer electronics, EVs and also home and system battery storage.

PROS: Advantages of high energy density and consequently lightweight design in comparison with other technologies, low self-discharge of about 1-2% in a month, high cell voltage and low maintenance make it ideal for different uses. The chemical/physical characteristics of Li-Ion batteries allow the design of different types tailored for different needs: from high current density type that is ideal for consumer mobile electronic equipment to higher current levels types, which are ideal for power tools, electric vehicles and also grid power applications.

CONS: Li-Ion cells and batteries are not as robust as some other rechargeable technologies and therefore need substantial protection/casing to protect them from physical damage. Besides, they also require overcharge and over-discharge protection and are prone to aging. At the moment one of the disadvantages is their high cost, which is expected to fall soon.

After analysis of various technologies, their parameters (technical and economics) and usability for COMPILE use cases, we choose the Li-Ion battery technology for our storage applications in pilot site Luče and Križevci.

VIRTUAL STORAGE - TECHNOLOGIES

The virtual storage term defines the storage capacity that is defined by one or more of the following characteristics:

• Non-stationary, like the EV battery where a location is changing.


• Capacity dependency on external parameters, for example of using house thermal inertia for flexibility. The heat-pump is stationary, but its available flexibility capacity is the weather, or user behaviour depended.

• Availability dependency on external parameters, for example in the industrial process the power of the machine is known, but the possibility to shut it down is depended on factory production and technological process.

Due to the above-described characteristics, the virtual storage is much more complex to operate and requires good ICT support and advanced algorithms for assessing the location, capacity, and availability of the storage/flexibility unit. To make these algorithms it’s important to have good forecasting models and techniques which are described in more detail in D3.1: Analysis, modelling and forecasting techniques and D3.2 Strategies for community-based managing of local energy consumption and production.

Virtual storage is a very promising field due to growing ICT supporting structure, a large number of already existing units that can be upgraded with low cost to support the ICT requirements needed for their participation and almost all the future technologies will be ready by default (EV, Heat-pumps, AC, home batteries,…).

The storage/flexibility units for virtual storage applications can be found in households, business buildings (offices, schools, health care, shopping malls, …), industry. with various technologies or process: heating, ventilation, air conditioning, hot water preparation, EV charging, …

The virtual storage can be used for ancillary services for TSO or DSO with the provision of demand response, load/production shifting, peak shaving, valley filling or it could be used just for optimization of consumers' energy costs.

EV charging

2.3.1.1 General information The battery of an electric vehicle (EV) is an energy reservoir, which can be used for the needs of various

actors such as prosumers, (distribution or transmission) system operators, balance responsible

parties, or aggregators.

In general, the term “reservoir” means an appliance that can be “filled” with energy, and the energy

stored in the reservoir can be “withdrawn from the reservoir” at any time. To enable such operation,

the reservoir shall have the capability to be charged (to receive the energy from an external system)

and discharged (to return the energy to the same external system). EV charging systems (either on-

board, installed in the EV, or off-board, installed outside of EV) currently available on the market do

not allow for discharging functionality. A “quasi” discharging functionality of EV charging system can

be achieved only when a battery with discharging capability is attached to the EV charging system (and

treated as a part of it); this configuration will not be implemented in any of COMPILE pilot sites and

will therefore not be described in this document.

In COMPILE, the EV charging systems that allow only charging (and not discharging) of EV batteries

will be implemented. However, the system allows filling the battery with different power during the

entire charging process. In this respect, the EV charging system acts as a virtual reservoir: the

difference between the actual load schedule (required by an external actor) from the planned one

(initial load schedule defined by EVRule) represents charging or discharging of a virtual reservoir

located in EV; the energy currently stored in this reservoir is available for later exploitation by an

external actor (prosumer, DSO, energy market actors; in COMPILE represented as HomeRule, GridRule

and ComPilot).


The initial (at the beginning of the charging session) energy stored in the reservoir is 0 kWh. At the

end of the charging session, the energy stored in the reservoir must reach 0 kWh; to fulfil this

condition, the positive deviations of actual charging load from the initially planned one, summed over

the entire charging session, must equal the sum of negative deviations, summed over the same time

interval. In this case, the delivered energy to EV battery till the end of charging session equals the

planned one, and the EV user’s needs (delivery of a required amount of energy till the end of charging

session) are satisfied despite modification (required by an external actor) of initial charging load

schedule planned by EVRule.

2.3.1.2 Technical characteristics of charging Physical values that characterise an individual charging session are:

• Wtot: amount of energy to be delivered to EV battery;

• Ttot: time available for charging;

• Pmax: maximum power that can be delivered to EV batteries. It is limited by the minimum of

rated powers of components that form the EV battery charging system (battery charger,

charging cable, charge point equipment) and of available power for charging (conditioned by

rated power of grid connection point, of cable that supplies the charge point and of

consumption of other consumers that are fed via the same grid connection point);

• Pmin: minimum power that can be delivered to EV batteries. In general, the minimum charging

power equals 0 kW (EV batteries not charging). Some charging infrastructure operators

control the charge points in the way that the EV is charged with at least minimum current (6 A

according to IEC 61851 standard, representing 1,4 kW at single-phase, and 4,1 kW at three-

phase charging) till the required energy (Wtot) is delivered to EV. The reason for such planning

of charging load is the following: the 0 kW load set point communicated by charging station

to EV, while the charging has not yet begun or the required energy is not yet delivered to EV

means an interruption of charging. The EV can interpret this interruption as a problem in

power supply (grid, charging station’s equipment) and for security reasons doesn’t allow later

beginning or restarting of charging.

Preconditions for the exploitation of a virtual reservoir are:

• maximum charging power Pmax is higher than the average one (Pavg). Average charging power

is a continuous power that allows for the delivery of energy, required by the EV user (Wtot),

during the time available for charging (ttot):

𝑃𝑎𝑣𝑔 = 𝑊𝑡𝑜𝑡

𝑡𝑡𝑜𝑡 (1)

• minimum charging power Pmin is lower than the average charging power Pavg.

The above conditions can be expressed as follows:

𝑃𝑚𝑎𝑥 > 𝑃𝑎𝑣𝑔 > 𝑃𝑚𝑖𝑛 or (multiplied by ttot) 𝑃𝑚𝑎𝑥 ∗ 𝑡𝑡𝑜𝑡 > 𝑊𝑡𝑜𝑡 > 𝑃𝑚𝑖𝑛 ∗ 𝑡𝑡𝑜𝑡 (2)

2.3.1.3 Charging scenarios In the planning of EV charging load schedules, three basic scenarios are used:

• Forced charging: the EV battery is charged as soon as possible. The charging load is set to Pmax

till the Wtot is delivered to EV. After delivery of Wtot the charging is ended (Pmin = 0 kW);

• Postponed charging: the EV battery is charged as late as possible. Charging begins with Pmin

and raises to Pmax when needed to deliver the Wtot till the end of the charging session (expiry

of ttot).


• Continuous charging: the EV battery is charged continuously with Pavg from the beginning to

the end of the charging session (expiry of ttot);

Examples of basic scenarios are presented in Figure 1:

Figure 1: Basic scenarios of EV charging load scheduling

Initial planning of the charging load is usually based on:

• forced charging (especially in public charging scenarios): to enable satisfying EV user’s needs

as soon as possible and release the charging station for use of the next customer;

• continuous charging: to burden as less as possible the public or prosumer’s internal network

with EV charging peak power.

2.3.1.4 Technical characteristics of virtual reservoir A deviation of charging power (and of delivered energy) from the initial charging plan represents, from

point of view of an external actor, charging or discharging of a virtual reservoir located in the EV and

made available for exploitation of external actor. Under this assumption, charging of EV battery with

a power higher than the planned one represents filling the reservoir with energy (the delivered energy

is higher than the planned one), while charging with a power lower than the planned one represents

emptying the reservoir.

A virtual reservoir can be described by the following parameters:

• P+: maximum power of reservoir filling. In each time point (interval) it corresponds to the

difference between Pmax and initially planned charging power (Pplan):

𝑃+ = 𝑃𝑚𝑎𝑥 − 𝑃𝑝𝑙𝑎𝑛 (3)

• P-: maximum power of reservoir emptying. In each time point (interval) it corresponds to the

difference between initially planned charging power (Pplan) and Pmin:

𝑃− = 𝑃𝑝𝑙𝑎𝑛 − 𝑃𝑚𝑖𝑛 (4)

• amount of energy currently stored in the reservoir (Wres): it corresponds to the integral of

differences between real (Preal) and planned (Pplan) load schedule values. The energy currently

stored in the virtual reservoir can be positive or negative:

𝑊𝑟𝑒𝑠 = ∫ (𝑃𝑟𝑒𝑎𝑙 − 𝑃𝑝𝑙𝑎𝑛) 𝑑𝑡𝑡

0 (5)

The energy stored in the virtual reservoir at the beginning of charging session is considered to

be 0 kWh. The same value must be reached at the end of charging session:

∫ (𝑃𝑟𝑒𝑎𝑙 − 𝑃𝑝𝑙𝑎𝑛) 𝑑𝑡𝑡𝑡𝑜𝑡

0 = 0 (6)


The maximum amount of energy that can be stored in the reservoir (either positive W+ or

negative W-) depends on the charging session’s characteristics (Wtot, ttot, Pmax and Pmin), to

initial charging load schedule (Pplan) and to required (real) load schedule (Preal).

Initially planned continuous charging

The initial charging plan corresponds to charging with average power (Pavg) from the beginning till the

end of the charging session (ttot) – see Figure 1 (yellow line):

𝑃𝑝𝑙𝑎𝑛 = 𝑃𝑎𝑣𝑔 =𝑊𝑡𝑜𝑡


Maximum power of reservoir filling (maximum real power exceeds the planned power):

𝑃+ = 𝑃𝑚𝑎𝑥 − 𝑃𝑝𝑙𝑎𝑛 = 𝑃𝑚𝑎𝑥 − 𝑃𝑎𝑣𝑔 = 𝑃𝑚𝑎𝑥 −𝑊𝑡𝑜𝑡


Maximum power of reservoir emptying (minimum real power is below the planned power):

𝑃− = 𝑃𝑝𝑙𝑎𝑛 − 𝑃𝑚𝑖𝑛 = 𝑃𝑎𝑣𝑔 − 𝑃𝑚𝑖𝑛 =𝑊𝑡𝑜𝑡

𝑡𝑡𝑜𝑡− 𝑃𝑚𝑖𝑛 (9)

The maximum amount of energy that can be stored in the reservoir:

𝑊+ = 𝑊− = 𝑡𝑡𝑜𝑡 ∗𝑃+∗ 𝑃−

𝑃++ 𝑃− (10)

During a charging session, only one of both values (W+ or W-) can be reached, and under additional

condition that forced or postponed charging scenario, as described in section 2.3.1.3, is applied as real

(required) charging load.

When forced charging is implemented as a real charging load schedule, the energy stored in the

reservoir is always positive. The Pmin equals 0 kW (charging stops after the battery is filled with Wtot).

The maximum amount of energy that can be stored in the reservoir equals:

𝑊+ = 𝑊𝑡𝑜𝑡 ∗ (1 − 𝑃𝑎𝑣𝑔

𝑃𝑚𝑎𝑥) (11)

When postponed charging is implemented as a real charging load schedule, the Pmin > 0 kW. The energy

stored in the reservoir is always negative. The maximum amount of energy (W-) that can be stored in

the reservoir amounts to the value calculated according to equation (10). If the charging load

scheduling allows to completely postpone the charging (Pmin = 0 kW till the EV begins charging with

Pmax), the maximum amount of energy (W-) that can be stored in the reservoir amounts to the value

calculated according to equation (11).

Figure 2, Figure 3 and Figure 4 present the energy stored in the reservoir during a charging session.

The simulation is made under the following assumptions:

• Continuous charging is planned as the initial load schedule

• Energy required by EV user: Wtot = 66 kWh

• Time available for charging: ttot = 8 h

• Initial charging load schedule: Pavg = 8,25 kW (during the entire charging session - 8 hours)

• Maximum possible charging load: Pmax = 22 kW

• Minimum possible charging load: Pmin = 3,67 kW

(applicable only when postponed charging is selected as real charging scenario)


When forced charging with 22 kW is required to be executed, the energy stored in the reservoir

increases until the EV battery is filled with Wtot (66 kWh), and decreases back to 0 kWh till the end of

the charging session:

𝑃+ = 𝑃𝑚𝑎𝑥 − 𝑃𝑎𝑣𝑔 = 22 − 8,25 = 13,75 kW

𝑃− = 𝑃𝑎𝑣𝑔 − 𝑃𝑚𝑖𝑛 = 8,25 − 0 = 8,25 kW

Maximum energy stored in the reservoir is:

𝑊+ = 𝑡𝑡𝑜𝑡 ∗𝑃+ ∗ 𝑃−

𝑃+ + 𝑃−= 8 ∗

13,75 ∗ 8,25

13,75 + 8,25= 41,25 kWh

Figure 2: Energy storage at planned continuous charging and actual forced charging

When postponed charging is required to be executed, the energy stored in the reservoir decreases till

the charging load jumps from Pmin to Pmax, and increases back to 0 kWh till the end of the charging

session.

𝑃+ = 𝑃𝑚𝑎𝑥 − 𝑃𝑎𝑣𝑔 = 22 − 8,25 = 13,75 kW

𝑃− = 𝑃𝑎𝑣𝑔 − 𝑃𝑚𝑖𝑛 = 8,25 − 3,67 = 4,58 kW

The maximum energy stored in the reservoir is:

𝑊− = 𝑡𝑡𝑜𝑡 ∗𝑃+ ∗ 𝑃−

𝑃+ + 𝑃−= 8 ∗

13,75 ∗ 4,58

13,75 + 4,58= 27,50 kWh

Figure 3: Energy storage at planned continuous charging and actual postponed charging

In practice, the demand response system that exploits the flexibility of EV charging may require also a

loaded schedule that deviates from a forced or postponed charging scenario. In this case, the


maximum reservoir capacity never reaches its theoretical maximum (or minimum). The energy stored

in the reservoir turns from increase to decrease and vice versa according to the current charging

power (above or below the planned one):

Figure 4: Energy storage at planned continuous charging and actual combined charging

Initially planned forced charging

The initial charging plan corresponds to forced charging as presented in Figure 1 (blue line). Charging

starts and continues with Pmax until the Wtot is delivered to the EV battery; after that, the charging ends

(Pmin = 0 kW). The energy stored in the virtual reservoir is always zero or negative.

When continuous charging with Pavg is implemented as a real charging load schedule, the maximum

amount of energy (W-) that can be stored in the reservoir is the same as in the case of initially planned

continuous charging and real forced charging. It is calculated according to equation (11).

When postponed charging is implemented as a real charging schedule, the calculation of the maximum

amount of energy (W-) that can be stored in the reservoir depends on the overlapping of maximum

charging load (Pmax) of the initial (forced) and real (postponed) charging schedule.

The time (measured from the beginning of the charging session) when the planned load decreases to

0 kW, equals:

𝑡1 = 𝑊𝑡𝑜𝑡

𝑃𝑚𝑎𝑥 (12)

The time (measured from the beginning of the charging session) when the real load increases to Pmax,

equals:

𝑡2 = 𝑃𝑚𝑎𝑥∗𝑡𝑡𝑜𝑡−𝑊𝑡𝑜𝑡

𝑃𝑚𝑎𝑥 −𝑃𝑚𝑖𝑛 (13)

The maximum amount of energy that can be stored in the reservoir is calculated as follows:

𝑊− = {𝑡1 < 𝑡2 ; 𝑊𝑡𝑜𝑡 ∗ (1 − 𝑃𝑚𝑖𝑛 𝑃𝑚𝑎𝑥⁄ )

𝑡1 > 𝑡2 ; 𝑃𝑚𝑎𝑥 ∗ 𝑡𝑡𝑜𝑡 − 𝑊𝑡𝑜𝑡} (14)

To avoid calculation of t1 and t2 and comparison of both values, the equation (14) can be expressed

also as:

𝑊− = MIN {𝑊𝑡𝑜𝑡 ∗ (1 − 𝑃𝑚𝑖𝑛 𝑃𝑚𝑎𝑥⁄ ) ; 𝑃𝑚𝑎𝑥 ∗ 𝑡𝑡𝑜𝑡 − 𝑊𝑡𝑜𝑡} (15)


If the charging load scheduling allows to completely postpone the charging (Pmin = 0 kW till the EV

begins charging with Pmax), the maximum amount of energy (W-) that can be stored in the reservoir

equals:

𝑊− = MIN {𝑊𝑡𝑜𝑡 ; 𝑃𝑚𝑎𝑥 ∗ 𝑡𝑡𝑜𝑡 − 𝑊𝑡𝑜𝑡} (16)

Figure 5, Figure 6 and Figure 7 present the energy stored in the reservoir during a charging session.

The simulation is made under the following assumptions:

• Forced charging is planned as the initial load schedule

• Energy required by EV user: Wtot = 66 kWh

• Time available for charging: ttot = 8 h

• Average charging load: Pavg = 8,25 kW

• Initial charging load schedule: Pmax = 22 kW (till delivery of Wtot - 3 hours)

• Maximum possible charging load: Pmax = 22 kW

• Minimum possible charging load: Pmin = 3,67 kW

The energy stored in the reservoir decreases until the planned load drops to 0 kW and increases back

to 0 kWh till the end of the charging session.

When continuous charging with Pavg is required to be executed, the maximum energy stored in the

reservoir reaches:

𝑊− = 𝑊𝑡𝑜𝑡 ∗ (1 − 𝑃𝑎𝑣𝑔

𝑃𝑚𝑎𝑥) = 66 ∗ (1 − 8,25 22⁄ ) = 41,25 kWh

Figure 5: Energy storage at planned forced charging and actual continuous charging

When postponed charging is required to be executed, the maximum energy stored in the reservoir

reaches:

𝑊− = MIN {𝑊𝑡𝑜𝑡 ∗ (1 − 𝑃𝑚𝑖𝑛 𝑃𝑚𝑎𝑥⁄ ) ; 𝑃𝑚𝑎𝑥 ∗ 𝑡𝑡𝑜𝑡 − 𝑊𝑡𝑜𝑡}

𝑊− = MIN {66 ∗ (1 − 3,66 22⁄ ) ; 22 ∗ 8 − 66}

𝑊− = MIN {55 ; 110} = 55 kWh


Figure 6: Energy storage at planned forced charging and actual postponed charging

In practice, the demand response system that exploits the flexibility of EV charging may require also a

loaded schedule that deviates from a continuous or postponed charging scenario. In this case, the

maximum reservoir capacity never reaches its theoretical minimum. The energy stored in the reservoir

turns from increase to decrease and vice versa according to the current charging power (above or

below the planned one):

Figure 7: Energy storage at planned forced charging and actual combined charging

TYPES AND PURPOSE OF STORAGE IMPLEMENTED IN COMPILE

Pilot site Luče

2.4.1.1 Real storage A battery energy storage system (BESS) is installed near to the transformer station which feeds the consumers in the village. The battery capacity is 333 kWh, maximum output power is 150 kVA.

In addition, five home battery systems with the following characteristics were installed:

• 2 x with a capacity of 22 kWh and maximum output power of 10 kW (existing),


• 1 x with a capacity of 10 kWh and maximum output power of 5 kW (within COMPILE),

• 1 x with a capacity of 6,5 kWh and maximum output power of 4 kW (within COMPILE).

These systems will be integrated with COMPILE tools for home energy management.


2.4.1.2 Virtual storage (EV charging) One AC charging station, connected directly to the public grid, is installed in Luče. The station is

intended for public use by residents and visitors. The charging station enables the charging of one EV

at a time with rated maximum power of 22 kW (limited to 17 kW due to grid constraints).

Also, 9 existing private AC charging stations (installed in households) with a rated maximum power of

22 kW each will be integrated with COMPILE tools for home energy management.

Pilot site Križevci

2.4.2.1 Real storage Two lithium-ion batteries will be installed in Križevci Technology Park to be used for surplus storage

and advanced energy management of the PV panels installed in the buildings as part of COMPILE. The

capacity of each battery is 9,8 kWh and the maximum charge/discharge power is 5,0 kW.

2.4.2.2 Virtual storage (EV charging) One AC charging station, connected directly to the public grid, is installed on the parking place in

Križevci Technology Park. The station is intended for public use by residents, employees and visitors.

The charging station enables the charging of two EVs at a time with a maximum power of 22 kW each.

3 REAL STORAGE IN KRIŽEVCI

GENERAL INFORMATION

Križevci is a small city in the central part of Croatia, around 60 kilometers northwest of Zagreb.

DCTP (Development Centre & Technology Park) Križevci is a business organization established to

stimulate entrepreneurship, innovation and economic development in Križevci, and, as an incubator,

to assist small entrepreneurs in the initial phase of the development. DCTP realizes tasks from the

Strategy for the Development of the City of Križevci. The Development Centre and Technology Park

are managed by Križevci Entrepreneurial Centre Ltd., which is in turn owned by the Municipality.


Figure 8: Križevci Technology Park

DCTP operates in five buildings of the former Stjepan Lacković Military Barracks in the centre of

Križevci with a total area of 8,490 m2.

The main building (where PV is installed and is integrated into COMPILE tools), has a total area of

3,175 m2 and consists of a research laboratory and common facilities for entrepreneurs – meeting

rooms, a conference hall, equipment for reproduction, projections, etc. The building also houses

management offices, special offices for entrepreneurs, a café, an exhibition area for new products and

innovations of entrepreneurs from the Technology Park, and a reception desk.

Four additional buildings with a total area of 5,135 m2 have modern, furnished offices for newly

established and existing companies with their own connection to electricity, water, gas, telephone,

Internet, and sanitary facilities. They are divided into modules of various sizes that can be used by

small and medium-sized entrepreneurs under favorable terms.


Figure 9: Aerial view of the five buildings of the Križevci Technology Park

The storage system consists of two LG RESU10 batteries that will be installed in the main building of

the Technology Park. Each battery has the following main characteristics:

• Cell type: Lithium-ion,

• Total energy: 9.8 kWh (usable: 8.8 kWh),

• Battery capacity: 189 Ah,

• Nominal voltage: 51.8 V,

• Voltage range: 42.0 ~ 58.8 V,

• Maximum charge/discharge power: 5.0 kW (peak power for 3 seconds: 7.0 kW).

The aforementioned batteries will be connected to an SMA Sunny Island 6.0H inverter whose main

specifications are:

• Maximum AC current for increased self-consumption (grid operation): 20 A,

• Maximum AC power for increased self-consumption (grid operation): 4.6 kVA,

• Maximum AC input current: 50 A,

• Maximum AC input power: 11.5 kW,

• Rated input voltage: 48 V,

• Maximum battery charging current: 110 A.

The overall system will be controlled by two SMA Home Manager 2.0 together with three SMT Control

Counters. This control system will provide local measuring, analysis, and management of the overall

system, including a basic control of battery charging and discharging.


Real storage in Križevci will be integrated into HomeRule together with other assets (energy meters,

PV production, etc.) in the Technology Park, as part of the portfolio of premises managed by the EnC.

Measurements from the inverters will be gathered via Modbus; while the PV inverter (ABB TRIO-20.0)

has Modbus communication capacity integrated, the storage inverter can be accessed with this

protocol using an additional piece of hardware (SMA Modbus Protocol Interface).

As of October 2020, the storage system has been purchased but not yet installed. The specific details

of its installation — physical location, grid connection, communication with the devices, etc. — are

already decided, so the installation will begin in November.

ARCHITECTURE

The details of the hardware installation are unknown at the submission of this deliverable.

Nevertheless, an approximate depiction of the final hardware architecture — based on a typical

configuration of PV and storage, together with actual information on additional equipment to be

installed — can be found in Figure 10.

Figure 10: Križevci Technology Park storage system overview

The different elements in the system architecture are:

• PV installation: 30 kW PV plant at the rooftop of the Technology Park. It was built in 2018 as

the first PV plant in Croatia crowdfunded by citizens. It is used for self-consumption within the

facility, which hosts around 30 organisations;

• PV inverter: 3-phase ABB TRIO-27.6 solar inverter, connected to the PV plant. The inverter has

built-in Modbus communication capability;

• Batteries: Two 9.8 kWh LG RESU10 batteries, as described in section 3.1;

• Storage inverter: SMA Sunny Island 6.0H. It does not comprise any communication interfaces

for third parties, only for other SMA devices;


• Modbus interface: SMA Modbus Protocol Interface. It provides a Modbus communication for

other SMA devices, including SMA Sunny Island;

• SMX: ETRA’s IoT gateway. Built over BeagleBone Black board, it can communicate with other

devices via serial port (RS-232, RS-485, and digital inputs) using the Modbus protocol, and to

the Internet via Ethernet, Wi-Fi, and 3G. In the case of the Technology Park, it will periodically

read data from the PV and storage inverters and send the readings in JSON format over MQTT

to HomeRule;

• SMA Sunny Home Manager: Local meter and controller for battery storage;

• Load: General load of the building, including HVAC system, lighting, outlets, etc.;

• EV charger: Installed in the premises of the Technology Park as part of COMPILE. More

information is provided in Chapter 5;

• Energy meter: A total of 8 meters installed in the main building of the Technology Park

measure the imported and exported energy in different areas of the premises. The output of

the PV and storage installation will be connected to one of the meters, while another one is

dedicated to the EV charger. An additional meter at the DSO substation serves as a sort of

control for the consumption of the whole Technology Park. None of the meters has

communication capabilities for third parties;

• RTU: A dedicated SAE net-line FW-5 station controller per meter will be used to periodically

read energy values from them and send the data to HomeRule.

Three main actors have been identified in the present scenario:

• Križevci Entrepreneurial Centre Ltd., as manager of the DCTP,

• Zelena energetska zadruga (ZEZ), as manager of the PV plant and the storage system, and

• Hrvatska elektroprivreda (HEP ODS), the Croatian DSO, which manages the distribution

network, including the transformer substation and the lines to the Technology Park.

The metrics gathered from the site will be sent via MQTT to HomeRule (through COMPILE ESB). The

Technology Park, already set up in the tool, appears in the GUI of the tool as one of the premises of

the EnC in Križevci, as seen in Figure 11.

Figure 11: Križevci Technology Park in HomeRule


Once the storage system is set up and readings gathered from the different measuring points and

devices, the data will appear in the different sections of the tool, as well as considered as inputs for

the internal optimization algorithms.

Figure 12: Križevci Technology Park detail in HomeRule

Analogous procedures will be performed in the rest of the premises considered in Križevci to gather

data from the devices installed in the buildings and send them to HomeRule.

PROCESS FLOWS AND ALGORITHMS

External process flow diagram and interfaces

Figure 13 shows a diagram of the external process flow of HomeRule, particularized for the case of

Križevci Technology Park:


Figure 13: HomeRule external process flow for Križevci Technology Park

The processes represented in the diagram can be classified into periodical and event-based.

Processes that are triggered periodically are:

1. The SMXs read from the PV and storage inverters and send the measurements to COMPILE

ESB using MQTT. HomeRule is subscribed to these messages, which, upon reception, are

stored in HomeRule’s internal repository. Estimated frequency of readings: every 10-15

seconds.

2. The RTUs read from the different energy meters in the building and send the measurements

to HomeRule in the same way as the SMXs. Estimated frequency: every 15 minutes.

3. External sources are queried periodically to obtain different data. All communication with

these external sources takes place using REST web services via TCP/IP, and the results are sent

to the COMPILE ESB using AMQP protocol:

• Weather forecasts from weatherbit.io. Data include temperature, relative humidity,

atmospheric pressure, cloud coverage, precipitation probability, and solar radiation.

Service is queried once per hour and provides forecasts for the next 48 hours.

• Spot prices from ENTSO-E’s transparency platform. The service provides energy prices

per country for the next day. As the availability of the price information varies per

country, the service is queried twice per day.

• Demand and production forecasts from ENTSO-E’s transparency platform. The same

restrictions and frequency as for spot prices apply.


4. Measurements from the EV charging stations controlled by EVRule are periodically sent to

COMPILE ESB for HomeRule to integrate and consider in its internal operation.

Communication is performed using the AMQP protocol.

5. HomeRule sends periodically measurements from all its controlled assets to GridRule and ComPilot via COMPILE ESB. Communication is performed using the AMQP protocol.

The following procedures are event-based:

6. EVRule sends information about its operation planning when a new schedule is set or a change

in a previously established schedule has occurred. Communication is performed using the

AMQP protocol.

7. ComPilot sends information on energy and network use tariffs whenever a new tariff is

created or an existing one is modified. Communication is performed using the AMQP protocol.

8. When a modification in the demand profile of the assets managed by HomeRule is required

(e.g. due to network restrictions or to optimize the portfolio of the EnC), a negotiation takes

place between the tool and the requester of flexibility (GridRule or ComPilot). Communication

is performed using the AMQP protocol.

More information on the interfaces with other COMPILE tools (process flows 5 to 8) is available in D2.4

Report on interoperability guidelines.

Internal process flow diagram, interfaces, and control algorithms

The internal process flow of HomeRule is presented in Figure 14:

Figure 14: HomeRule internal process flow

Internal modules represented in Figure 14 are described in detail in D2.2 System architecture, while

the control algorithms are presented in D3.2 Strategies for community-based managing of local energy

consumption and production. A summary of the processes is provided below.

HomeRule’s real-time monitor is subscribed to COMPILE ESB for different types of data, including

energy measurement (consumption, production, storage, etc.) from the field, energy and weather


forecasts, and energy prices, as described in section 3.3.1. For these subscriptions, MQTT and AMQP

protocols are used, over TCP/IP.

New data arrive periodically (PF 1). As soon as it is received, it is stored in the different repositories of

the tool (PF 2): the last values overwrite the previous ones in the operational database — so the

current status is maintained — while they are added to the long-term database to keep track of the

historical evolution of each metric. Data is stored using specific protocols of each database

management system (MongoDB for operational, InfluxDB for long-term).

Every 15 minutes, the KPI engine reads the last received information from the long-term DB (PF 3) and

performs a series of calculations, including metric consolidation (maximum, minimum, and average

values per period) and advanced energy performance indicators. These calculations are stored back

in the repositories for subsequent access.

With the same periodicity, the facility energy optimizer module (PF 4) crosschecks different types of

information stored in the database (energy models, calendar schedule, tariff data, etc.) to calculate

the values of the setpoints of the controllable assets (storage included) managed by HomeRule that

perform the best results (i.e. optimize) for the objective established by the operator. These setpoints

are stored in the database as well as sent to the facility asset dispatcher module (PF 5), which

transforms them into actual commands to be sent to the assets via COMPILE ESB (PF 6) using MQTT.

Another module, the demand response optimization framework, triggers a process every 15 minutes

(PF 7) to check the current status of each controllable asset and calculate their individual flexibility.

This information is stored in case a request for flexibility arrives from other COMPILE tools via

COMPILE ESB (PF 8). The module manages the negotiation of the campaign, prompting the operator

in case their input is required. As a result of the negotiation, a new set of setpoints is generated and

passed along to the facility asset dispatcher module (PF 5). The demand response optimization

framework module is also responsible for communication with other COMPILE tools for additional

purposes, as explained in section 3.3.1.

Finally, all information from the repositories — and thus, the different modules of HomeRule — can

be queried by the operator from the tool’s GUI (PF 9). The access to the real-time monitor is done

using the Distributed Data Protocol (DDP), a client-server protocol that automatically propagates the

changes on the server to each of the subscribed clients; this keeps the data in the GUI updated at any

time. Access to the long-term repository is done using the specific DBMS protocol.

FACTORY TESTING

Besides the standard tests, the battery modules are fire tested against an explosion or sign of fire

when the battery cells are forced into a thermal runaway condition.

REQUIREMENTS FOR INSTALLATION AND COMMISSIONING

Communication with the local network (LAN) is required for the system’s proper operation.

The battery has the protection degree IP55, meaning that the product is protected against dust ingress

that could be harmful for the normal operation of the product, but is not fully dust-tight. It is protected

against solid objects and water jets projected by a nozzle (6.3 mm) from any directions. The BESS is

best to be placed inside the main distribution cabinet of the building, next to the inverter. Between

the battery and the grid, there is a 48 V SMA inverter required for battery management and

communication.

The following tests will be performed:


• Battery operation under maximum load when the full battery,

• Battery operation with excess solar with an empty battery,

• Battery operation under minimum load when the full battery,

• System response in case of grid loss,

• Battery operation in island mode - to verify that system components operate correctly without

endangering the rest of the building’s electrical components,

• Test run in real operation conditions.

REQUIREMENTS FOR USE

The storage system doesn’t require special maintenance or supervision of operation; its operation is fully automated. It is required to execute daily monitoring and monthly visual inspection.

4 REAL STORAGE IN LUČE

GENERAL INFORMATION

In Luče, a Battery Energy Storage System (BESS) is connected directly to the transformer station of the

local DSO Elektro Celje.

Figure 15: BESS installed in Luče

The Luče BESS is manufactured by Qinous GmbH. The energy capacity of BESS is 333 kWh; the rated

power of the system is 150 kVA. The BESS is integrated with Petrol GridRule.

The physical location of the BESS is next to the transformer station. The connection is done through a

smart motorised switch inside the transformer station which also serves as a disconnection point for

the DSO. Figure 16 shows the connection point with the smart switch:


Figure 16: BESS connection point inside the transformer station

In addition, 5 home battery systems, installed in households, will be integrated with the COMPILE

system. Technical characteristics are as follows:



• 1 x with a capacity of 10 kWh and maximum output power of 5 kW (within Compile),

• 1 x with a capacity of 6,5 kWh and maximum output power of 4 kW (within Compile).

The operation of 5 home battery systems will be integrated with HomeRule for home energy management. Functionalities of HomeRule related to control of home battery systems are described in D3.2 Strategies for community-based managing of local energy consumption and production, Chapter 5).

Figure 17 shows a household battery system in 5 different locations.


Figure 17: Household battery systems

ARCHITECTURE

Figure 18 presents a hardware architecture of the battery storage system. The green area marked with

“I” represents the non-air-conditioned area, a blue area marked with “II” represents the air-

conditioned area.


Figure 18: BESS system overview

Components in the non-air-conditioned area are:

• K: Temperature and humidity control devices, which include air conditioning, water pumps,

dry cooler heat exchanger,

• 5: Transformer, converts voltage from the inverter to the grid voltage.

Components in the air-conditioned area:

• 1: Mains connection, point where the battery storage is connected to the grid,

• 2: Overvoltage arrestor, a safety device for protection of overvoltages like lightning strikes,

• A1: Auxiliary power supply. Used for powering the control units in case of grid failure,

• A2: Auxiliary power supply via mains connection. Powering control units in case of circuit

breaker (marked with number 4) tripping,

• 3: Switch disconnector for disconnecting power from HVAC units and control units,

• 4: Circuit breaker for disconnecting/protecting the power components of the battery storage

unit,

• 6: LCL Filter for correcting the sinusoidal shape of the voltage and reduces the level of

harmonics at the grid connection point,

• 7: Inverter used to convert DC voltage to AC or AC to DC, capable of generating energy in all

four quadrants,

• 8: Insulation monitoring device,

• 9: Battery system, where the energy is stored from the grid,

• B: Power supply for the control part of the battery energy storage system,

• C: Programable logic controller that controls all parts of the battery energy storage system

(HVAC, inverter and batteries),

• D: Communication connection point to the local internet provider with a mobile provider as a

backup in case of the main connection failure.


Figure 19 presents three main components that compose the battery energy storage system: HVAC,

power converting and battery storage.

Figure 19: BESS internal components

BESS communicates with all nine sites where HomeRule is installed. The communication with

HomeRules is done through Modbus TCP/IP communication protocol. The collected information

displayed in the BESS user interface is presented in Figure 20.

BESS collects only the vital information that is important for the management of the grid. The majority

of data from HomeRules is collected in the SCADA system.

Figure 20: Home energy management system (HomeRule)

Figure 21 presents all HomeRule sites connected to one of the three output lines of the transformer

station. All the sites communicate through a virtual private network.


Figure 21: Integrated assets in GridRule

GridRule integrates BESS, smart switches in the transformer station, SCADA system, TANGO platform

and AI models as can be seen in Figure 21.

BESS is used for the execution of GridRule commands with the main functionality to store energy to

BESS or discharge energy to the grid. Smart switches measure the state of the grid in the transformer

station and allow the GridRule to disconnect their users from the main grid and operate in island

mode.

All available data is collected from various devices in the SCADA system via Modbus TCP/IP protocol.

From the SCADA, vital data is transferred to the TANGO platform via the OPC UA communication

interface. TANGO platform shares the data collected in the SCADA systems with all interested parties

through custom dashboards and application programming interfaces. At the same time, commands

for GridRule and HomeRules are received from the Tango platform and transmitted to the SCADA

system which forwards it to appropriate devices via Modbus TCP/IP protocol.

AI models are used to predict grid behaviour by forecasting local PV production and user consumption.

AI model calculates setpoints at which BESS should operate with the help of grid behaviour forecasts

according to the predictions from AI models. Data from GridRule is transmitted to HomeRule sites

where they are used to influence site behaviour to optimise the common operation of all sites under

the GridRule.


Process flow (control) diagram

To control the operation of BESS in Luče, advanced forecasting algorithms are deployed to include as

much RES production as possible on a microgrid level in a weak local grid and to reduce curtailing of


RES production due to local over/under voltage with the help of COMPILE tools GridRule and

HomeRule. GridRule with cooperation with HomeRule can increase RES production penetration with

the help of a BESS that operates with the support of accurate advanced forecasting algorithms

developed in GridRule. Forecasts are derived from live actual measurements (from smart meters,

home energy management systems, battery energy storage systems and historical data stored in

TANGO), sent via the SCADA control system. Petrol developed TANGO, a monitoring platform with

advanced dashboarding used for monitoring of various systems.

Figure 22: Luče storage process flow

External interfaces

Within the pilot site Luče, data from IoT devices and measurements from BESS, households, renewable

production units and household battery data is transferred to TANGO through SCADA via Modbus

TCP/IP protocol. Communication from the SCADA to smart meters in households and BESS is

transferred via Modbus TCP/IP protocol. Data transferred from SCADA to end units are forecasted set

points and control data. Data is sent to enable forecasting capabilities of end units in order to fulfil

demand based on variable PV production based on weather data forecasts in order to maximize the

penetration of renewable sources and maximize self-sustainability in the local grid.

Weather forecast data provider transfers weather forecast data to the TANGO platform via TCP/IP and

REST API communication interface. Weather forecast data provider ARSO provides a local forecast for

solar irradiation, temperature, snowfall, air pressure, freezing level, wind speed, wind direction,

relative humidity, snow level and rainfall on an hourly basis. Three days ahead forecast is used in the

Production and consumption forecast module. The forecast module provides a power flow forecast

for households and power flow from transmission lines in Luče connected to the transformer station

compensated by the Battery energy storage system.

Internal interfaces

Communication between modules encapsulated in GridRule between AI modules Production and

consumption forecast and BESS scheduler to and from TANGO is operated via TCP/IP and REST API

communication interface.

SCADA BESS

Households

TANGO

Production and

consumption forecast module

BESS scheduler module

Weather forecast provider

GridRule

HomeRule


Production and consumption forecast module collects weather forecast data with historical data of

production and consumption of electrical energy in pilot site from the TANGO tool to get forecast

models and predict production and consumption based on live measurements from TANGO. Predicted

production and consumption are transferred to and saved in TANGO. Predicted production and

consumption can be monitored in TANGO GUI.

Data on forecasted production and consumption are transferred from TANGO to the BESS scheduler

module together with live measurement data from the BESS and power flows in the power grid. With

the help of live measurement data and forecasted data, the BESS scheduler module sets the optimal

set point for the BESS for the next three days and is refreshed every 15 minutes by the latest

measurement and forecast data available to the GridRule. An optimal set point for the BESS is

transferred from the BESS scheduler module to TANGO.

Figure 23: BESS scheduler module, Production and consumption forecast module results with actual flow

Results of BESS scheduler module, Production and consumption forecast module for one day are

presented in Figure 23, with the goal of maximal implementation of renewable resources, PV

production units by increasing demand in hours with the highest production and discharging in hours

with the highest demand in order to provide self-sufficiency to the village and prepare for next sunny

day based on weather forecast data.

Interfaces to COMPILE tools

Interface to COMPILE tool GridRule is done by SCADA and TANGO. From the SCADA vital measurement

data is transferred to the TANGO platform via the OPC UA communication interface. At the same time,

commands for GridRule and HomeRule are received from the Tango platform and transmitted to the

SCADA system which retransmits it to other devices via Modbus TCP/IP protocol.


Internal control algorithms

Battery energy storage systems can charge and discharge in order to help end consumers, distribution

system operators, local grid and other various actors. In the pilot site Luče Battery energy storage

system can charge and discharge according to GridRule’s set point. If communication with GridRule is

not available, BESS can operate according to its own control algorithms including:

• Peak load shaving manager,

• Self-sufficiency & island mode,

• Zero set point,

• Follow set point.

BESS switches from Follow set point mode into the desired control algorithm Self-sufficiency & island

mode if there is no available forecast for the current period, if the model was not refreshed with the

set point forecast older than specified, or if the communication between SCADA, TANGO and BESS is

not available for more than desired period to ensure reliable forecast of production, consumption and

optimal set point for energy storage in the system.

FACTORY TESTING

Before shipment, BESS had to be tested by the manufacturer and make sure the unit performs as

expected. The mayor tests executed before shipment were:

• Visual checks to verify that all the equipment is installed correctly as specified by

documentation;

• Initialization of devices. All smart devices are initialized correctly:

o Programmable logic controller has the correct software loaded,

o Router has the correct communication settings,

o Inverter is set to correct mode with correct settings,

o HVAC system is set up and operational;

• Run a preliminary check on the battery racks, to verify if all the battery cells are inside the

expected voltage ranges;

• Check if all the digital and analog inputs and outputs are connected properly to the

programable logic controller according to the documentation;

• Load test, to see if there are any problems when operating at a maximum power of +/- 150

kVA. Figure 24 shows the successful execution of the test.

Figure 24: Load test

• Thermal test, to determine if the installed HVAC system operates correctly and is capable of

cooling installed components sufficiently. The most critical components are Inverter and LCL


filter in Figure 25 we can see the HVAC system in the thermal test cools the LCL filter to an

acceptable level of 80°C in four minutes.

Figure 25: Thermal test LCL filter

• In Figure 26 we can see the room temperature of the battery compartment in the same thermal test as in Figure 26. We can see in the picture that the room is cooled to an acceptable level of 25°C in 4 minutes after starting the HVAC unit.

Figure 26: Thermal test room temperature

• Full charge and discharge of the battery at maximum power: full charge and discharge cycle must be done to assure that BESS can perform at required power levels in the whole range of state of charge. In Figure 27 we can see the test performed and the system performing at expected -+ 150 kW power levels.

Figure 27: Full cycle test



Technical requirements

Technical requirements needed to be fulfilled before the commissioning:

• BESS is installed on its designated spot, according to manufacturer specification,

• Grid connection is established to the BESS,

• Communication connection with smart switches inside the transformer station,

• Communication interface is established with all the Home rule installations,

• Virtual private network is established with Qinous headquarters for commissioning purposes.

• Smart switches in the transformer station are properly configured for the collection of

measurement data and their management.

Non-technical requirements

As a preparation for the BESS installation quite a few non-technical requirements needed to be met

to fulfil all the legal and regulatory requirements.

The following documents are needed to be prepared:

• Project file with all the requirements for installation of BESS,

• Project for Execution (PFE) for the connection of BESS in Transformer station,

• Project conditions from DSO and other stakeholders (Ministry) were received,

• Fire safety plan,

• Lightning bolt plan,

• Plan of building structures,

• Security plan.

The following consents and permits needed to be obtained:

• DSO consent for connection of BESS to the grid,

• Environment agency permit for BESS installation,

• Municipal consent for BESS installation,

• Neighbours consent for BESS installation,

• Opinion on the project by Water and Sewage Municipal services company,

• Construction permit.

Field tests

After installation of BESS on site, the following Site acceptance tests (SATs) were performed:

• Start/Stop of BESS on site:

o Purpose: to check if BESS is responding to commands trough HMI,

o Preconditions: BESS is stopped/BESS is in operation mode,

o Pass/fail criteria: BESS goes to operation mode/BESS is stopped;

• Start/Stop of BESS – remote control:

o Purpose: to check if BESS is responding to the remote control – commands trough

SCADA,

o Preconditions: BESS is stopped/BESS is in operation mode,

o Pass/fail criteria: BESS goes to operation mode/BESS is stopped;

• Charging/Discharging of BESS:

o Purpose: to check if BESS is responding set points for charging/discharging,

o Preconditions: BESS is operating in default mode and the set point for charging /

discharging is set trough HMI or trough remote control,


o Pass/fail criteria: BESS starts to charge /discharge based on the set setpoint +/- 5%;

• Round trip efficiency (RTE):

o Purpose: to check BESS round trip efficiency,

o Preconditions: BESS SoC is at 5%,

o Pass/fail criteria: Difference between Measured RTE and Theoretic RTE should be less

than 2%.

Figure 28: Results of BESS RTE test

• Zero load provision:

o Purpose: to check if BESS can provide zero load provision through transformer station,

o Preconditions: BESS SoC is between 20% - 80%,

o Pass/fail criteria: BESS is ensuring zero load provision trough Transformer station, max

+/- 10 kW power flow is allowed through the transformer station;


Technical requirements for operation of BESS:

• Outside temperature range -30°C to +40°C,

• Outside Humidity 100% condensing,

• Maximum inverter current is 216 A at 450 V, after these values are exceeded the inverter will

trip after a set time delay,

• Short circuit level is 381 A at 450 V where the inverter will trip immediately after this value is

exceeded,

• Normal grid voltage required for operation is 400 V +-10%,

• Communication connection with smart switches inside the transformer station,

• Communication connection with all the Home rule installations,


• Smart switches in the transformer station are properly configured for the collection of

measurement data and their management,

• Communication interface is established with the TANGO platform from where the commands

are received for Grid rule operation.

Maintenance intervals as required by the manufacturer:

• Monthly:

o Check air intake filter (not air-conditioned area), wash if required;

• Half-yearly:

o Check the battery room for any type of smoke, the smell of chemicals or leaks,

o Check the system carefully for condensation,

o Check for changes in electrical properties;

• Yearly:

o Visual check of electrical installations,

o Check residual current devices using the test button,

o Visual inspection of the inverter,

o Inspection for unusual noises and odours of the inverter,

o Check for conductive dirt or steam (especially with insulation materials) and clean if

necessary,

o Inverter check coolant connections,

o Inverter check all screw connections (electrical and mechanical) and tighten if

necessary (torque wrench required),

o Check fan and filter of the control cabinet and replace if necessary,

o Container visual inspection for mechanical damage,

o Container if necessary, carry out paint repairs to ensure corrosion resistance,

o Container check and/or adjust the door seal to maintain the IP protection class,

o Transformer visual inspection for mechanical damage and dirt.

5 VIRTUAL STORAGE – EV CHARGING

GENERAL INFORMATION

In Luče, one charging station is installed on the public parking place and integrated via EV Rule and

ESB with the COMPILE system (Petrol GridRule). The station’s technical and functional characteristics

are:

• Intended use: public,

• Electrical connection: directly to the public grid,

• Manufacturer: Etrel,

• Charging station type: INCH Pro,

• Charging station model: G-PC1ZBDZ40,

• Mounting: self-standing (pole-mounted),

• Dimensions: 45 x 27 x 13,5 cm,

• Weight: 8,2 kg,

• Casing: Aluminium,

• Cover plate: Polycarbonate Lexan,

• Ingress protection: IP 56,

• Number of charge points (EVSE) per charging station: 1,

• Number of connectors per charge point (EVSE): 1,


• Connector type: socket-outlet, IEC 62196-2 Type 2, with plug locking,

• Rated voltage: 3 x 230 VAC,

• Maximum phase current: 32 A (corresponds to maximum charging power of 22 kW),

• Metering: MID certified energy meter,

• Electrical protection: DC leakage current detection (6 mA),

• Communication with EV: IEC 61851,

• Communication with EVRule: Ethernet and GSM 4G (LTE), communication protocol OCPP 1.6,

• Status indication: LED,

• User interface: touch screen 3,5’’,

• User identification: RFID card, or PIN code via the touch screen.

Figure 29: Charging station installed in Luče

Besides, 9 existing charging stations, installed in households, will be integrated with the COMPILE

system. The technical characteristics are the same as described above. Operation of stations will be

subordinated to HomeRule (see section 5.2, Subordinated EVRule); functionalities of HomeRule

related to control of charging stations are described in D3.2 Strategies for community-based managing

of local energy consumption and production, Chapter 5).

In Križevci, one charging station is installed and integrated via the EV Rule and ESB with the COMPILE

system (ETRA GridRule).

The station’s technical and functional characteristics are:

• Intended use: public,

• Electrical connection: directly to the public grid,

• Manufacturer: Etrel,

• Charging station type: Pole station G6,

• Charging station model: G-6232-0-0-A,

• Mounting: self-standing (foundation mounted),

• Number of charge points (EVSE) per charging station: 2,

• Number of connectors per charge point (EVSE): 1,

• Connector type: socket-outlet, IEC 62196-2 Type 2, with plug locking,

• Rated voltage: 3 x 230 VAC,

• Maximum phase current: 32 A (corresponds to maximum charging power of 22 kW),

• Metering: 2 x MID certified energy meter,

• Communication with EV: IEC 61851,


• Communication with EVRule: Ethernet and GPRS, communication protocol OCPP 1.6,

• User interface: LCD screen 147 x 58 mm,

• User identification: RFID card, smartphone app.

Figure 30: Charging station installed in Križevci

Operation of the station will be subordinated to GridRule (see section 5.2, Independent EVRule);

functionalities of GridRule related to control of charging station are described in D3.2 Strategies for

community-based managing of local energy consumption and production, Chapter 2).

SYSTEM ARCHITECTURE

EVRule, developed by Etrel, is used for monitoring and control of the operation of electric vehicle

charging infrastructure and to manage business processes related to EV charging.

The EVRule functionalities can be executed in two ways:

• Subordinated EVRule: EVRule is subordinated to and communicates with HomeRule. EVRule

functionalities are executed by the charging station itself. The subordinated EVRule will be

implemented in Luče (and will communicate with PETROL HomeRule);

• Independent EVRule: EVRule acts independently, i.e. communicates directly with GridRule

and ComPilot. Applicable in public charging (EVRule functionalities are executed by a

dedicated ICT tool — charging infrastructure control centre) or at home charging (EVRule

functionalities are executed by the charging station itself) without other controllable assets in

the final customer’s internal network, i.e. without HomeRule implemented. The independent

EVRule will be implemented in pilot sites Križevci (and will communicate with ETRA GridRule

and ComPilot) and Luče (and will communicate with PETROL GridRule).

Subordinated EVRule

A simplified architecture drawing for a scenario with a subordinated EVRule is presented in Figure 31.

All EVRule functionalities are executed by the EV charging station.

SW modules of the station, relevant for load management, are presented by grey boxes. Green circles

denote external actors (building owner, EV user, EV and HomeRule) while the arrows represent the

information data flow (the blue ones are related to the planning of charging schedules and the red

ones to the execution of charging load control).


Figure 31: Simplified architecture of EV charging system (subordinated EVRule)

For this scenario, the process flow will not be described since it is similar to the process flow in the

case of independent EVRule.

Independent EVRule

In the scenario with independent EVRule (mostly used in scenarios with public charging), a new

component (Charge Point Management System - CPMS) is introduced, which represent the Charge

Point Operator’s (CPO) back-end for control of charging sessions and support of its business activities.

It consists of the following main SW modules:

• charge points monitoring and control: acquisition of real-time information about charging

sessions and about the operation of charging stations, remote control of charge points’

operation;

• acquisition of EV users’ data in the case the charging stations are not equipped with

appropriate user interfaces (see section 5.3.2.2): the user communicates the mentioned data

via smartphone;

• management of EV user’s contracts and charging authorization: maintenance of EV users’

white lists, communication with external actors for charge point reservation and charging

authorization;

• billing: billing and tariff configuration supporting multiple pricing schemes and payment

options;

• reporting and analysis: overview overcharging sessions (energy delivered, parking time,

maximum power, charging costs), and over operation of charge points (events, utilization rate,

number of charging sessions and energy delivered during a selected time frame,…);


• asset management and maintenance support: information about charging stations (locations,

equipment installed, required maintenance intervals), work orders for regular maintenance

and extraordinary interventions;

• system configuration: charging infrastructure technical characteristics, communication

settings within charging system components and towards external actors, assignment of roles

and permissions to CPO’s staff for access to individual modules.

The CPMS can be implemented in two ways: as a hosted service in a cloud environment, or as a

licensed SW installed on CPO’s servers. The operating system of CPMS is Windows Server, application

SW is written in .net programming language. A sample of CPMS’s desktop is presented in Figure 32:

Figure 32: Charge Point Management System (operated by CPO)

In the scenario with independent EVRule, the charging station is not subject to development within

the COMPILE project; all EV charging load management functionalities (EVRule), specific for an EV

charging system that operates within the COMPILE environment, are developed as an upgrade of

CPMS. To simplify the terminology and descriptions, the term EVRule will be used for all functionalities

(SW modules) of CPMS: the general ones (intended for support of CPO’s business activities) and also

the ones specific for charging load management within the COMPILE system (EVRule).

A simplified architecture drawing for a scenario with an independent EVRule is presented in Figure 33.

EVRule functionalities are executed as a cloud-based CPO’s SW suite for the management of EV

charging infrastructure. SW modules of EVRule, relevant for load management, are presented by grey

boxes. Green circles denote external actors (EV user, EV, charging station, CPO and GridRule/ComPilot)

while the arrows represent the information data flow (the blue ones are related to the planning of

charging schedules and the red ones to the execution of charging load control).


Figure 33: Simplified architecture of EV charging system (independent EVRule)

The subordinated EVRule will not be implemented in any COMPILE pilot site. In addition, the process

flows and algorithms related to independent and subordinated EVRule are similar. Therefore, in the

continuation of this document, all descriptions relate to independent EVRule.


Actors and components involved in EVRule operation

Actors and components involved in EV charging system operation (see Figure 33) are electric vehicle

(EV), EV charging station, EV user, CPO that operates the EVRule, and COMPILE tools GridRule and

ComPilot.

Electric vehicle, precisely its on-board charger (AC/DC rectifier) with batteries represents a load,

controllable by charging station. The maximum power that can be drawn by EV is limited by the

number of phases and rated current of the on-board charger. Typically, the rated current is between

16 A and 32 A, which results in charging power between 3,7 kW and 7,4 kW (single-phase charging)

and between 11 kW and 22 kW (three-phase charging).

Charging station serves for an electrical connection between the grid and EV and control of EV

charging load. It also acquires EV user’s data (user ID, departure time – the time when the user intends

to disconnect the EV), which are communicated to EVRule to enable control of charging sessions and

charging energy management. Some charging stations are also capable (dependent on charging

station type) to acquire information about maximum power that can be drawn by connected EV.

EV user communicates to the system its user ID, the information about EV type that is intended to be

charged (this information is needed for determination of maximum achievable charging power), and

departure time. There are two ways of acquisition of this information (see sections 5.3.2.1 and

5.3.2.2): via charging station’s user interface, or by using a smartphone and communication with

EVRule.


EVRule (operated by CPO) controls the charging sessions and supports the CPO in its business

activities.

COMPILE tool GridRule and ComPilot: GridRule is used for monitoring and control of grid operation.

ComPilot serves for Energy Community management. Both tools manage the demand response

procedures: acquisition of information about assets’ operation and flexibility potential, activation of

flexibility offered by individual components of the COMPILE system (among them also by EVRule).

Concerning EVRule they act as a higher-level control entity that controls the EV charging load

according to conditions in the energy grid and market.

Interfaces between actors and components

5.3.2.1 Interface EV user – charging station The interface enables the EV user to identify (i.e. apply for charging by communicating the user ID)

and insert planned departure time (see section 5.3.3.1). The interface is relevant when the EV user

identifies (applies for charging) at the charging station (not at EVRule by smartphone). The

identification can be executed by an RFID card or by insertion of a PIN code on the station’s touch

screen. After identification, the user inserts the departure time. A sample of GUI for insertion of

information is presented in Figure 34:

Figure 34: Charging station’s user interface – Insertion of PIN code and departure time

5.3.2.2 Interface EV user – EVRule If the charging station is not equipped with an interface for identification (RFID card reader, touch

screen for insertion of PIN code or similar), the user identifies by a smartphone using a dedicated app.

On the geographical map the user selects the charging station to be used for charging, inserts the

departure time and confirms the application for charging:

Figure 35: Smartphone screen - Selection of charging station and insertion of departure time

If the charging is executed at a charging station that doesn’t enable automatic measurement of

maximum EV charging power (see section 5.3.3.1, the user inserts via smartphone also the EV type to


be used. The EV type is selected among the types that are already inserted in the EV user’s database

(the entire procedure is described in Chapter 8.

Via smartphone (or tablet), the EV user can also monitor the parameters of its charging session, as

presented in Figure 36:

Figure 36: Smartphone and tablet screens for monitoring of charging session

5.3.2.3 Interface CPO - EVRule The interface enables the CPO to manage EV users’ contract data, insert data (locations, technical

characteristics) about charging infrastructure and power supply limitations and monitor and control

the operation of charging infrastructure (see section 5.2.2).

5.3.2.4 Interface EVRule - charging station The interface serves for communication of user and charging session data from charging station to

EVRule, and for control of charging station’s operation by EVRule (remote start/stop, required load

schedule). For communication, the OCPP 1.6 protocol [1] via Ethernet or GPRS is used.

5.3.2.5 Interface charging station - EV During the entire charging session, the charging station converts the currently valid value of the

charging schedule to a load set point. The load set point is converted to a pulse-width modulated

signal (following IEC 61851 standard [2]; the duty cycle corresponds to maximum phase current that

can be drawn by EV). The signal is applied to a control pilot wire, which is integrated into the charging

cable that connects the charging station with the EV. According to the communicated duty cycle, the

EV battery management system controls the operation of the EV on-board charger.

5.3.2.6 Interface EVRule - GridRule/Compilot The interface is executed via ESB, using the communication protocol AMQP. It serves for execution of

demand response functionalities (communication of charging data and flexibility offers by EVRule, and

communication of flexibility requests and orders by GridRule/ComPilot). The details are given in D2.4

[3], Chapter 3.

EV charging process flow

The EV charging process flow consists of the following steps after the EV is connected to the charging

station:

• Step 1: Acquisition of EV and EV user data,


• Step 2: Verification of EV user’s contract validity,

• Step 3: Calculation of energy required by EV user,

• Step 4: Determination of maximum possible charging power,

• Step 5: Calculation of initial charging plan and flexibility potential,

• Step 6: Demand response negotiation,

• Step 7: Communication of charging schedule to charging station,

• Step 8: Communication of charging load set points to EV.

For the operation of the COMPILE-integrated charging energy management system the following

preconditions must be fulfilled:

• infrastructure settings: in EVRule, the data about charging infrastructure must be inserted:

power supply limitations (needed for step 4), location of stations, stations’ IDs;

• communication settings: data about communication network configuration (active

components, routers, URLs) must be inserted in EVRule;

• EVRule must contain data about EV users: user IDs (needed for steps 2 and 3), the validity of

contracts (needed for step 2), characteristics of EVs to be used by the user (optionally needed

for step 3);

• EVRule must contain data about past charging sessions of individual users: date, connection

time, duration, delivered energy (needed for step 3).

5.3.3.1 Step 1. Acquisition of EV and EV user data The data about EV and EV user, needed for efficient energy management, are:

• EV user ID,

• Departure time,

• Required energy,

• Maximum EV charging power.

The communication interface between EV and charging station, which is currently implemented in

both components, conforms to IEC 61851 standard [2]. Unfortunately, this standard allows only the

exchange of a restricted set of information (such as maximum allowed current that can be drawn by

EV on-board charger; this information is also used for charging load control) and signals to control the

charging process.

The new standard ISO 15118 [4] for communication between EV and charging station allows the

exchange of an extended set of information, among them also the above-listed data relevant for

energy management. Unfortunately, this standard is not yet implemented in the EVs; therefore, some

workarounds are needed for the acquisition or determination of data needed for the participation of

EV charging in demand response schemes.

EV user ID is a unique user identifier. At the beginning of charging, the EV user applies for charging by

communicating its ID to the charging system, usually via the charging station’s user interfaces (RFID

card reader, touch screen and insertion of PIN code). Afterwards, the charging station communicates

the user ID to EVRule. If the charging station’s user interfaces don’t enable the acquisition of EV user

ID, the EV user must apply for charging via smartphone (see Figure 33, blue dashed arrows), using the

dedicated app that communicates to EVRule the charging station’s ID and the EV user ID.

Departure time is the time when the EV user intends to disconnect the EV from the charging station.

In combination with the time when the user applies for charging, the departure time defines the time

available for charging, i.e. the time within which the required energy must be delivered to EV batteries.


The departure time is communicated to the charging system via the charging station’s touch screen

(see section 5.3.2.1) or via EV user’s smartphone (see section 5.3.2.2).

The required energy is the energy that must be delivered to EV batteries till the departure time. It is

calculated by EVRule (see section 5.3.3.3).

Maximum EV charging power is calculated as a minimum of rated (maximum) power of the following

components:

• Power supply to charging station,

• Charging station’s equipment,

• Cable that connects the EV and charging station,

• EV’s on-board charger.

Power supply to the charging station can be single- or three phases. The maximum power that can be

delivered to the charging station is defined by the rated current of power supply cable wires and

calculated by multiplication of this value with several phases and grid rated voltage (usually 230 V).

Within the parameterisation phase of the system, the parameter is inserted into the charging station’s

and EVRule’s configuration database (and thus known to charging station and EVRule).

The charging station’s equipment is usually three-phase. The information about the rated current of

switching equipment is parametrised during manufacturing (and thus known to charging station) and

also inserted to EVRule during parameterisation of the charging system.

The cable that connects the EV and charging station can be permanently attached to the charging

station or detachable. In the first case, the rated current of cable wires is parametrised during

manufacturing (and thus known to charging station). In the case of detachable cable, the user uses its

own cable. The plug on the charging station side is equipped with a resistor; the resistance is defined

by the rated current of the cable and can be read by the charging station.

EV’s onboard chargers are single- or three phases, with a defined rated current per phase(s). The

parameters are not known to the charging station. The information about the maximum power of the

EV onboard charger (in Figure 33 labelled as Pcharger.max) can be obtained in two ways:

• By charging station: immediately after the beginning of charging, the charging station meters

the power flow to EV and calculates the Pcharger.max;

• By EVRule (in Figure 33 indicated with a blue dashed arrow): if the charging station is not

capable to meter the maximum power flow to EV (and communicate it to EVRule), the EV user

must use the smartphone to apply for charging and at the same time to communicate to

EVRule the type of EV that will be charged. The procedure is described in ANNEX A: EVRULE -

INSTRUCTIONS FOR USE BY EV USERS (section 8.1.4). Based on the user’s information and

information about EVs stored in EVRule‘s database, the EVRule determines the parameters of

EV on-board charger and calculates the maximum possible EV charging power.

5.3.3.2 Step 2. Verification of EV user’s contract validity The user ID, acquired as described in section 5.3.3.1, is checked against the validity of the user’s

charging contract, associated with the user ID. If the contract is not valid, the charging session is

ceased, and the user is informed (via smartphone or charging station’s user interface) that the

application for charging service is rejected.

5.3.3.3 Step 3. Calculation of energy required by EV user The actual energy required by an EV user to be delivered to the EV battery is not known. This energy

amount depends on characteristics and conditions of the battery (rated capacity, current state of


charge) and on the user’s preferences (for example, in public charging, the user doesn’t want the

battery to be completely charged, because charging at home is cheaper). However, the information

about required energy, or more precisely about energy planned to be delivered to battery till

departure time, is mandatory for the determination of charging schedules and flexibility margins.

The option for the direct acquisition of information about required energy (similarly to insertion of

departure time via smartphone or charging station’s touch screen) is not implemented. At present,

most users are not in the position to completely understand the meaning of the term required energy

and to correctly estimate its value (in numerical terms – kWh). To overcome this lack of information,

the required energy is estimated by EVRule based on historical data about charging sessions executed

by the same user. Therefore, historical data about charging sessions must exist in the EVRule database

before the execution of any power management functionality.

Historical charging sessions’ data, relevant for the determination of required energy, are a time of

charging (date – day type, time), duration of charging and delivered energy. They are extracted from

operation (charging sessions) data communicated by the charging station to EVRule at the end of each

charging session. Based on these parameters the algorithm for calculation of required energy tries to

identify the user’s behaviour, usually characterised by seasonal and weekly mobility patterns (for

example regular weekly business or family obligations), which are then reflected in regular needs for

charging energy. When the user applies for charging, the algorithm executes statistical treatment of

archived data about past charging sessions that match with the user ID, current day type and current

time. The execution of statistical calculations results in an estimation of the user’s regular behaviour

pattern (energy delivered in a certain day type and time), which is extrapolated to the current charging

session.

To reduce the quantity of stored charging sessions data, raw data older than the predefined period

(12 weeks) are deleted. Information about user’s behaviour before this period is kept only indirectly

in form of resulting daily predictions for each characteristic type of the day.

5.3.3.4 Step 4. Determination of maximum possible charging power The maximum EV charging power, calculated as described in section 5.3.3.1, is not necessarily the

maximum power that is allowed to be delivered to EV. The maximum power that can be delivered to

the prosumer’s internal network is limited by the rated current of protection devices (fuses) at the

grid connection point. A part of this power is consumed by other appliances that operate in the

prosumer’s internal network. The maximum power that can be delivered to EV(s) is therefore limited

by the power available for charging (difference between the maximum power of grid connection point

and the estimated maximum consumption of other appliances). The value is inserted into EVRule

during the charging system parameterisation, and compared, at the beginning of each charging

session, with maximum EV charging power; the lower value prevails as the maximum possible charging

power (Pmax).

5.3.3.5 Step 5. Calculation of initial charging plan and flexibility potential When the user data (departure time, maximum possible charging power, required energy) are known,

the EVRule determines the initial charging plan (schedule). The target function is that the required

energy is delivered during the time available for charging (i.e. till departure time) with the power that

doesn’t exceed the maximum possible charging power.

In general, the charging system plans the charging in a way, that the required energy is delivered as

soon as possible. In this case, the charging starts with the maximum possible charging power and ends

when the required energy is delivered. When the charging load flexibility is offered to the flexibility


trading platform, the initially scheduled power can be reduced to allow to offer flexibility in both

directions (reduction and increase of load).

In the COMPILE system, consumption is labelled with negative values and production with positive

values. In this sense, the positive flexibility potential means the ability to decrease the charging load,

while the negative flexibility potential means the ability to increase the charging load.

The protocols used for communication with GridRule and ComPilot in relation to flexibility offers and

requests are described in D2.4 [3], Chapter 3. The flexibility offered or requested to be activated is

expressed as an average deviation of active power from the planned one during predefined time

intervals.

In this respect, the negative flexibility potential (ability to increase the charging load) is calculated as

a difference between Pplan and Pmax (where Pplan denotes the initially planned charging load determined

as described in section 5.3.3.5, and Pmax the maximum possible charging power calculated as described

in section 5.3.3.4). The positive flexibility potential (ability to decrease the charging load) corresponds

to Pplan.

5.3.3.6 Step 6. Demand response negotiation The process is described in D2.4 [3], sections 3.4 and 3.5. The result of the process is the requirement

for modification of the current charging load schedule (sent by GridRule or ComPilot to EVRule) which

must be communicated to the charging station.

5.3.3.7 Step 7. Communication of charging schedule to charging station The EVRule converts the required charging schedule into a form defined for communication of load

schedules to charging stations. For communication, the OCPP 1.6 protocol [1] is used.

5.3.3.8 Step 8. Communication of charging load set points to EV During the entire charging session, the charging station converts the currently valid value of the

charging schedule to a load set point and applies it to the communication interface towards EV. The

communication of load set points is described in section 5.3.2.5.

If at departure time communicated by EV user to EVRule (as described in section 5.3.3.1) the EV user

doesn’t disconnect the EV from charging station, charging continues with maximum possible charging

power (see section 5.3.3.4) until the EV battery is fully charger or till the user disconnects its EV from

charging station.

5.3.3.9 Clustered charging stations If several charging stations are installed at the same location and fed from the same grid connection

point, the EVRule algorithms must be enhanced with additional functionalities:

• in the determination of maximum possible charging power (step 4, calculated as described in

section 5.3.3.4), common for all clustered stations, the EVRule must consider internal

limitations of a cluster of charging stations (rated power of a common power supply to a

cluster of stations might not be sufficient to charge all connected EVs with maximum power);

• in the calculation of charging schedules, the EVRule must distribute (disaggregate) the

maximum possible charging power (or the charging power required by GridRule/ComPilot) to

individual simultaneously charged EVs. In this process, the EVRule must consider the EV users’

needs (required energy, departure time) and characteristics of their EVs (maximum power of

onboard chargers). The target function is that the user needs (delivery of required energy till

departure time) are satisfied for all charging sessions without violation of maximum total

possible charging load. If this is not possible, the users are treated in a non-discriminatory


way: the charging plans are calculated in the way that the violations of user needs (i.e.

percentage of non-delivered energy at departure time) are equally distributed among all

users. Consequently, step 5 (Calculation of initial charging plans) must be enhanced with

disaggregation feature, and the same process must be applied also between step 6 (Demand

response negotiation) and step 7 (Communication of charging schedules to charging stations).

FACTORY TESTING

Testing of solutions to be implemented at pilot sites will be executed in three phases:

• Component tests,

• Interface and closed-loop lab tests,

• Field tests.

The first two groups of testing (component and interface lab tests) are executed in the laboratory

environment. Information about field testing is given in section 5.5.3.

Component tests

Component tests will be conducted in a laboratory environment, mostly with simulated inputs and

outputs to the charging system (EV and EV user data, inputs and outputs to the COMPILE system via

interfaces between charging station and EVRule, and EV rule and GridRule/ComPilot).

Components and processes of charging stations that are already developed (e.g. acquisition of data

from EV and EV user, a large part of data exchange between charging station and EVRule) are tested

according to standard procedure. The tests related to charging station are:

• Visual inspection of charging station: surface, painting, the connection of wires to terminals;

• Verification of proper operation of user interfaces (displays, LED lights, RFID card reader);

• Verification of proper reaction to signals from EV (cable connected, vehicle ready for

charging);

• Verification of accuracy of metering devices by charging via artificial load;

• Testing of connectivity (Ethernet, WiFi, GPRS) with external component (EVRule);

• Verification of proper execution of basic processes (identification, start/stop charging, load

control).

In this phase, testing of EVRule’s functionalities is executed by real EV charging and simulation of data

exchange with GridRule/ComPilot:

• Verification of proper creation of messages to be sent to GridRule/ComPilot related to

measurements, operation planning and demand response process (see D2.3 [3], Chapter 3);

• Verification of proper interpretation of messages received from GridRule/ComPilot related to

demand response process (see D2.3 [3], sections 3.4 and 3.5);

• Algorithms testing: verification of the proper operation of algorithms (determination of

maximum charging power, determination of charging schedules, calculation of flexibility

margins).

• Verification of proper operation of algorithms: calculation of maximum possible charging

power and flexibility margins, and determination of charging schedules. Load schedules (basic

and modified according to demand response requirement) shall result in delivery of required

energy before or till the expiry of time available of charging and shall not exceed maximum

power available for charging;

• Verification of proper storage of process data in EVRule’s database.


Interface and closed-loop lab tests

Interface lab tests will be conducted in the laboratory, under conditions as much as possible similar to

the real operation (connected EVs, real users, real connection between EVRule and

GridRule/ComPilot). In this phase, the interfaces between GridRule/ComPilot and field devices (grid

components) are simulated. The tests will contain:

• verification of correct communication connectivity (URLs, envelopes and messages’ headers);

• verification of correct structure of exchanged data (data field names, formats and cardinality);

• verification of correct interpretation and processing of demand response process data

received from GridRule/ComPilot.

Closed-loop lab testing is executed in a complete COMPILE environment with verification of correct

execution of the entire energy management process, proper operation of charging system operator’s

and EV users’ GUI, and correct visualization of results of the demand response process.

The main subject of closed-loop lab testing is a verification of charging load control. This test is not

site-specific: the algorithms implemented in EVRule for the execution of COMPILE functionalities are

the same for all pilot sites and all micro-locations (prosumers). The tests under various conditions

(configuration of charging stations, EVs’ technical characteristics) will be performed in a lab

environment. At pilot sites the tests will not be repeated on a full scale by simulating a complete range

of possible charging scenarios; a proper operation will be verified during the observation period (till

the end of the project) when the real users will use the charging stations.

Successful closed-loop lab tests represent the Factory Acceptance Test (FAT). Satisfactory results

(confirmed by final users – pilot site managers) related to all EVRule’s functionalities signify that the

system is ready to be implemented at pilot site(s).


Installation

In general, charging stations are classified into two groups (Figure 37): wallboxes (usually with one

connector) and pillars (usually with two or more connectors).

Figure 37: Types of charging station (wallbox – left, pillar – right)

As regards the installation of charging stations, two types are common: wall mounting (indoor) and

foundation mounting (outdoor).

The installation of a wallbox on the wall is simple and can be executed by non-professionals. Outdoor

installation of a pillar (also stations of wallbox type can be installed outside using a special supporting

construction) is more complex and requires the execution of civil works for a foundation, cable trench

for power supply cables and (optionally) protective rails. Samples of outdoor installation with a sketch

of the foundation are presented in Figure 38:


Figure 38: Outdoor installation of charging station

A requirement for the obtainment of a construction permit for outdoor installation depends on the

location (private/public place) and local legislation.

The basic installation of the charging station requires a space of approximately 650 mm x 400 mm. If

the charging station is installed together with the safety rail, the dimensions of the required space are

approximately 850 mm x 450 mm. Usually, air vents are built into the station. Air vents must not be

blocked or obstructed by other items or objects. When applicable, air vents must be protected from

being covered with snow.

The power supply must sustain the rated current of 32 A/phase for single-connector stations, and 63

A for double-connector stations. The cross-section of wires depends on the material of the conductor,

and cable length between the distribution box and charging station.

System setup

Once the charging stations are installed and connected to the local power supply, they are ready to

be used for charging the EVs. To use the full functionality of charging stations and to be able to exploit

their demand response capabilities they shall be connected to the backend/operating system

(EVRule). This will allow to group charging stations to clusters, manage their power, send load

schedules to charging stations, modify sessions’ power while considering user needs, allowing EV

users’ interaction with the charging process via mobile app, etc.

Before the EVRule begins to execute its main task (charging load control under the needs of grid

operation and power market), the entire charging system must be configured and some preliminary

data shall be present in the EVRule’s charging sessions database.

5.5.2.1 System setup and configuration The system configuration, relevant for COMPILE functionalities, consists of EVRule setup and

establishment of communication connectivity between the charging stations and EVRule.

System setup is executed at three levels: site level, prosumer level and EV user level.

At the site level, one cloud instance is established for each location (Luče, Križevci). Within each

location, a hierarchical load area scheme is defined to enable treatment (load control, reporting, etc.)

of charging sessions at an individual prosumer, group of prosumers (e.g. the ones being fed from one

transformer or power line) or entire charging infrastructure of an individual site.

At the prosumer level, the system setup requires the insertion of information related to charging

stations and power supply:

• location information: address, GPS coordinates, working time, access conditions (public,

private, identification modes) and other basic information;

• number of stations installed at prosumer and number of charge points at each station,


• connection type of each station (one- or three-phase),

• maximum power (current) that can be delivered via each charging phase,

• internal (prosumer’s) networking inside the building: total capacity of the grid connection

point, maximum power available for charging, ratings of fuses and cables that feed individual

charging stations.

EV user-level contains the information about users’ names, addresses, means of identification (e.g.

RFID card, PIN code, smartphone, SMS) with associated IDs, and EV types intended to be used by the

user.

5.5.2.2 Communication setup Communication between charging stations and EVRule is internet-based. EVRule is running in the

cloud. As a physical layer ethernet, WiFi or GPRS can be used.

The establishment of connectivity is based on proper configuration (setup) of communication

parameters in EVRule and in charging stations (IP addresses of stations and routers, the opening of

appropriate ports for bidirectional communication EVRule – charging station).

Field tests

Once the charging stations are installed at the pilot site and the EVRule is configured, the following

verifications will be executed:

• Communication connectivity between components,

• System functional settings: presence of correct and sufficient data about charging

infrastructure, power supply and EV users,

• Algorithm for calculation of required energy,

• Charging load control.

The initial communication test between the charging station and EVRule is done from the EVRule

where the charging station is pinged and communication ports are tested whether they are open and

messages from EVRule can reach the station. Even if communication diagnostics show no errors or

malfunctions a verification shall be done whether the communication is stable and consistently

working. This is done by checking the heartbeat signals sent from the charging station to EVRule in a

predetermined time frame (default time frame is 5 minutes).

Testing of communication between EV user and EVRule (via smartphone) is executed in order to verify

if the charging stations are properly presented on the geographical maps and if the information

(identification data, departure time) linked to individual charging session is properly communicated

to EVRule.

System functional settings are tested indirectly: if any information is insufficient, the system will report

an error or warning with a description of the cause of the malfunction.

The energy required by EV users is calculated by EVRule based on users’ behaviour in the past. To

enable this calculation, historical data about charging sessions must exist in EVRule’s database before

the execution of any power management functionality. The database will be continuously updated

with data on new charging sessions and the accuracy of prediction should increase, which will be

monitored during the entire system operation.

Charging load control is tested with a complete COMPILE system in operation. As regards the EV

charging part of the system, the following requirements apply:

• All other tests (communication, functional testing, algorithms) must be successfully executed,


• All conditions valid for normal use (see Chapter 8) must be fulfilled,

• The departure time should be set at least 4 hours from the beginning of charging,

• The battery must not be fully charged; charging with maximum power for at least two hours

should be possible.


For the operation of charging stations, the system (grid) voltage shall not violate the standard margins

defined by grid codes valid for the location and voltage level in question.

The communication between the charging station and EVRule must be established and stable. In the

opposite case:

• Charging is enabled only if the EV user identifies at charging station via RFID card or PIN code,

not via smartphone,

• Power management functions are disabled.

Any malfunction of charging system operation is detected by EVRule and reported to CPO in form of

error logs and warnings. Therefore it is recommended to continuously check these reports and logs.

In general, the charging stations don’t require special maintenance or supervision of operation; their

operation is entirely automated. It is recommended to execute a yearly visual inspection (potential

humidity in the enclosure, the brightness of display …) and manual triggering (test button) of operation

of protection devices.

Requirements for use for EV users are given in Section 8 ANNEX A: EVRULE - INSTRUCTIONS FOR USE

BY EV USERS.

6 CONCLUSIONS

Storage technologies (battery energy storage and EV charging systems), which are or will be installed

at COMPILE pilot sites Križevci and Luče, are upgraded with functionalities that will enable their

maximum contribution to the achievement of goals of respective energy communities.

The design, as presented in this deliverable, allows full integration of storage systems with COMPILE

building (HomeRule) and grid (GridRule) energy management systems; in this way, the developed

control functionalities of storage systems will significantly contribute to the achievement of a higher

level of reliability of local grid operation, to increased penetration of renewable energy sources’

production and optimisation of costs associated with power production and supply to final customers.

Besides the integrated operation within the COMPILE environment, the storage systems are also

capable to operate in independent mode, without being functionally linked to subordinated GridRules

and HomeRules. In this operation mode, the systems execute safety functions such as load shedding,

voltage and frequency control (as in the case of BESS installed in Luče) or adaptation of consumption

to parameters of building’s internal network (as in the case of EV charging).

The main equipment of storage systems is already installed (BESS in Luče, and EV chargers in Luče and

Križevci); installation of BESS in Križevci is in progress and will be finished by end 2020. In parallel,

activities in the field of testing and integration of developed solutions with other COMPILE tools are

conducted to enable the timely beginning of the trial operation.

The results of activities of T3.3 represent a quality foundation for later project activities directly

related to deployment and operation of various systems at pilot sites (T3.4 Software integration, WP5

Pilot sites and WP6 Impact assessment). Furthermore, the presented functionalities of storage


systems will support the energy communities and grid operators at pilot sites in the development of

business models which will lead to the achievement of their goals set within the project.


7 REFERENCES AND ACRONYMS

REFERENCES

[1] Open Charge Alliance, “https://www.openchargealliance.org/protocols/ocpp-16/,” [Online].

[2] IEC 61851-1 Electric vehicle conductive charging system - Part 1: General requirements, IEC, 2017.

[3] “D2.4 Report on interoperability guidelines,” COMPILE project, 2019.

[4] ISO 15118-2 Road vehicles - Vehicle to grid communication interface - Part 2: Network and application protocol requirements, ISO, 2014.

ACRONYMS

Abbreviations and Acronyms list

AC Alternating Current

AI Artificial Intelligence

AMQP Advanced Message Queuing Protocol

API Application Programming Interface

app (smartphone) application

BESS Battery Energy Storage System

ComPilot COMPILE ICT tool for EnC management

CPMS Charge Point Management System

CPO Charge Point Operator

CRM Customer Relationship Management

DBMS DataBase Management System

DC Direct Current

DCTP Development Centre & Technology Park (Križevci)

DSO Distribution System Operator

EnC Energy Community

ENTSO-E European Network of Transmission System Operators (for electricity)

ESB Enterprise Service Bus

EV Electric Vehicle

EVRule COMPILE ICT tool for operation and management of EV charging infrastructure

EVSE Electric Vehicle Supply Equipment

GPRS General Packet Radio Service (linked to GSM)

GPS Global Positioning System

GridRule COMPILE ICT tool for operation and management of (micro) grid

GSM Global System for Mobile Communications

GUI Graphical User Interface

HMI Human-Machine Interface

HomeRule COMPILE ICT tool for the operation of building’s internal network

HVAC Heating, Ventilation, and Air Conditioning

ICT Information and Communication Technologies

ID IDentifier

IEC International Electrotechnical Commission


Abbreviations and Acronyms list

IoT Internet of Things

ISO International Organization for Standardization

LAN Local Area Network

LCD Liquid Crystal Display

LCL Inductance-Capacitance-Inductance

LED Light-Emitting Diode

LES Local Energy System

LTE Long-Term Evolution standard (linked to GSM)

MID Measuring Instruments Directive (2014/32/EU, 2015/13/EU)

MQTT MQ Telemetry Transport (standard for IoT messaging)

OCPP Open Charge Point Protocol

OPC UA Object linking and embedding for Process Control Unified Architecture

PF Process Flow

PIN Personal Identification Number

PV PhotoVoltaic

REST Representational State Transfer

RFID Radio Frequency IDentification

RTE Round Trip Efficiency

RTU Remote Terminal Unit

SCADA Supervisory Control And Data Acquisition

SMS Short Messsage Service

SMX ETRA’s IoT gateway

SoC State of Charge

SW Software

TCP/IP Transmission Control Protocol/Internet Protocol

URL Uniform Resource Locator

WiFi Wireless Fidelity


8 ANNEX A: EVRULE - INSTRUCTIONS FOR USE BY EV USERS

GENERAL REQUIREMENTS

To assure a proper operation of EVRule (calculation of EV user required energy, determination of load

flexibility range, enabling the remote charging load control) the preconditions described below must

be fulfilled.

Adding EV types to be used by EV user

If the charging station manufactured by Etrel is used, the entire section 8.1.1 is not applicable.

After the EV user is registered in the system by the CPO or by the EV user himself via the web app, the

EV types (with EV charger data: maximum charging current per phase, number of phases) that will be

used by this user must be stored in the EVRule database.

8.1.1.1 Adding a new EV type via smartphone web app In the smartphone web app select the "username" and "My vehicle":

Select “Add new vehicle”:


Select the vehicle type (Make, Model, Version) and click “Save vehicle”:

When the EV type is added, the EV data (number of phases, minimum and maximum EV charger phase

current) is automatically assigned to it. Check if the data is correct: minimum charging current (AC

charging min current) should be 13 A for Renault ZOE model year 2012-2015, 10 A for Renault ZOE

model year 2015- and 6 A for all other EV types; data about maximum charging phase current (usually

10, 16 or 32 A) and a number of charging phases can be found in user manuals for EVs.

If necessary, manually modify data and click “Save vehicle”:

When all EV types that will be used by EV users are inserted, one of them (the one that will be most

frequently used) must be selected as a Default vehicle.


Select the vehicle, confirm it as the default vehicle and click “Save vehicle”:

8.1.1.2 Adding a new EV type via Ocean GUI In the Ocean GUI select the CRM module and “Users”. Select "User vehicles" and "Add" button:

When the EV type is added, the EV data (number of phases, minimum and maximum EV charger phase

current) are automatically assigned to it. Check if the data are correct: minimum charging current (AC

charging min current) should be 13 A for Renault ZOE model year 2012-2015, 10 A for Renault ZOE

model year 2015- and 6 A for all other EV types; data about maximum charging phase current (usually

10, 16 or 32 A) and several charging phases can be found in user manuals for EVs.

If necessary, manually modify data and click “Save vehicle”:


When all EV types that will be used by EV users are added, one of them (the one that will be most

frequently used) must be selected as the Default vehicle.

Select the vehicle that will be charged:

Confirm this vehicle as Default:


Identification of EV user before charging

If the charging station manufactured by Etrel is used, this section is not applicable.

EV user must apply for charging (i.e. identify) via smartphone, not by RFID card:

Insertion of departure time

At identification, the EV user must specify the departure time (i.e. the time when he plans to

disconnect the EV from the charging station) via smartphone (left) or charging station (right):

Selection of EV type to be charged

If the charging station manufactured by Etrel is used, this section is not applicable.

For each charging session, the EVRule needs the data about EV that will be used for charging to

determine charging load flexibility margins (minimum and maximum charging power – see section

8.1.1). The EV that was selected as Default EV in the process of adding EV types for individual EV users

(see sections 8.1.1.1 and 8.1.1.2, last figure) is automatically assigned to all charging sessions of the

respective EV user.

If the EV user intends to charge another EV type (not defined as Default EV in his profile), the EV type

that is going to be charged must be selected before the connection of EV to the station.

In the smartphone web app select the vehicle, confirm it as default and select “Save vehicle”:


Documents

D3.3 Advanced models and technologies of local storage and